Upload folder using huggingface_hub

0.codes.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fd65b6c4f5d54eb1c6beaedb280aba70512c4852e12114f95a843ee666e5de0c
-size 3637020
+oid sha256:5e27e6f70b31f876ceb85ad9290ffd8f755d180440e5d15a585e65ba97f9fbd8
+size 3640540

0.metadata.json

@@ -1,6 +1,6 @@
 {
     "passage_offset": 0,
-    "num_passages": 5310,
-    "num_embeddings": 908968,
+    "num_passages": 5315,
+    "num_embeddings": 909850,
     "embedding_offset": 0
 }

0.residuals.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:72b9010d7dfed1b25f2aa3f51f5b7275c334cbaa7ffb31d02e998c63dd5b1ffd
-size 58175152
+oid sha256:cbe4544d7f28aa63c75e0344eec1f1ac9991eff35d27337b3a92098dd86d3f63
+size 58231600

buckets.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:67237f7216df9b38debae0ff3f3e88ea2c2629d65fd72b51c98702a92ddfcd96
+oid sha256:4a346979c8e6ad004b4552ecaecbf6691a83b46aa3689cc2f5f40fff02227010
 size 1432

centroids.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:de57e0f7ffb8412d4259b2ef3d51063fef821cf0616e80eea79bcc3230790e6d
+oid sha256:ff885ac897f130b58bc96d70f875a9a9a0842b36f9c70cb4964e62cbe53ce642
 size 2098342

collection.json

@@ -5308,5 +5308,10 @@
   "Instruction tuning commonly means finetuning a language model on instruction-response pairs. We discover two forms of adaptation (tuning) that are deficient compared to instruction tuning, yet still yield instruction following; we call this implicit instruction tuning. We first find that instruction-response pairs are not necessary: training solely on responses, without any corresponding instructions, yields instruction following. This suggests pretrained models have an instruction-response mapping which is revealed by teaching the model the desired distribution of responses. However, we then find it's not necessary to teach the desired distribution of responses: instruction-response training on narrow-domain data like poetry still leads to broad instruction-following behavior like recipe generation. In particular, when instructions are very different from those in the narrow finetuning domain, models' responses do not adhere to the style of the finetuning domain. To begin to explain implicit instruction tuning, we hypothesize that very simple changes to a language model's distribution yield instruction following. We support this by hand-writing a rule-based language model which yields instruction following in a product-of-experts with a pretrained model. The rules are to slowly increase the probability of ending the sequence, penalize repetition, and uniformly change 15 words' probabilities.",
   "We support this by hand-writing a rule-based language model which yields instruction following in a product-of-experts with a pretrained model. The rules are to slowly increase the probability of ending the sequence, penalize repetition, and uniformly change 15 words' probabilities. In summary, adaptations made without being designed to yield instruction following can do so implicitly.",
   "In the era of large language models (LLMs), a vast amount of conversation logs will be accumulated thanks to the rapid development trend of language UI. Conversation Analysis (CA) strives to uncover and analyze critical information from conversation data, streamlining manual processes and supporting business insights and decision-making. The need for CA to extract actionable insights and drive empowerment is becoming increasingly prominent and attracting widespread attention. However, the lack of a clear scope for CA leads to a dispersion of various techniques, making it difficult to form a systematic technical synergy to empower business applications. In this paper, we perform a thorough review and systematize CA task to summarize the existing related work. Specifically, we formally define CA task to confront the fragmented and chaotic landscape in this field, and derive four key steps of CA from conversation scene reconstruction, to in-depth attribution analysis, and then to performing targeted training, finally generating conversations based on the targeted training for achieving the specific goals. In addition, we showcase the relevant benchmarks, discuss potential challenges and point out future directions in both industry and academia.",
-  "In addition, we showcase the relevant benchmarks, discuss potential challenges and point out future directions in both industry and academia. In view of current advancements, it is evident that the majority of efforts are still concentrated on the analysis of shallow conversation elements, which presents a considerable gap between the research and business, and with the assist of LLMs, recent work has shown a trend towards research on causality and strategic tasks which are sophisticated and high-level. The analyzed experiences and insights will inevitably have broader application value in business operations that target conversation logs."
+  "In addition, we showcase the relevant benchmarks, discuss potential challenges and point out future directions in both industry and academia. In view of current advancements, it is evident that the majority of efforts are still concentrated on the analysis of shallow conversation elements, which presents a considerable gap between the research and business, and with the assist of LLMs, recent work has shown a trend towards research on causality and strategic tasks which are sophisticated and high-level. The analyzed experiences and insights will inevitably have broader application value in business operations that target conversation logs.",
+  "Scaling model size significantly challenges the deployment and inference of Large Language Models (LLMs). Due to the redundancy in LLM weights, recent research has focused on pushing weight-only quantization to extremely low-bit (even down to 2 bits). It reduces memory requirements, optimizes storage costs, and decreases memory bandwidth needs during inference. However, due to numerical representation limitations, traditional scalar-based weight quantization struggles to achieve such extreme low-bit. Recent research on Vector Quantization (VQ) for LLMs has demonstrated the potential for extremely low-bit model quantization by compressing vectors into indices using lookup tables.   In this paper, we introduce Vector Post-Training Quantization (VPTQ) for extremely low-bit quantization of LLMs. We use Second-Order Optimization to formulate the LLM VQ problem and guide our quantization algorithm design by solving the optimization. We further refine the weights using Channel-Independent Second-Order Optimization for a granular VQ. In addition, by decomposing the optimization problem, we propose a brief and effective codebook initialization algorithm. We also extend VPTQ to support residual and outlier quantization, which enhances model accuracy and further compresses the model.",
+  "In addition, by decomposing the optimization problem, we propose a brief and effective codebook initialization algorithm. We also extend VPTQ to support residual and outlier quantization, which enhances model accuracy and further compresses the model. Our experimental results show that VPTQ reduces model quantization perplexity by 0.01-0.34 on LLaMA-2, 0.38-0.68 on Mistral-7B, 4.41-7.34 on LLaMA-3 over SOTA at 2-bit, with an average accuracy improvement of 0.79-1.5% on LLaMA-2, 1% on Mistral-7B, 11-22% on LLaMA-3 on QA tasks on average. We only utilize 10.4-18.6% of the quantization algorithm execution time, resulting in a 1.6-1.8times increase in inference throughput compared to SOTA.",
+  "In this paper, we introduce MIO, a novel foundation model built on multimodal tokens, capable of understanding and generating speech, text, images, and videos in an end-to-end, autoregressive manner. While the emergence of large language models (LLMs) and multimodal large language models (MM-LLMs) propels advancements in artificial general intelligence through their versatile capabilities, they still lack true any-to-any understanding and generation. Recently, the release of GPT-4o has showcased the remarkable potential of any-to-any LLMs for complex real-world tasks, enabling omnidirectional input and output across images, speech, and text. However, it is closed-source and does not support the generation of multimodal interleaved sequences. To address this gap, we present MIO, which is trained on a mixture of discrete tokens across four modalities using causal multimodal modeling. MIO undergoes a four-stage training process: (1) alignment pre-training, (2) interleaved pre-training, (3) speech-enhanced pre-training, and (4) comprehensive supervised fine-tuning on diverse textual, visual, and speech tasks.",
+  "MIO undergoes a four-stage training process: (1) alignment pre-training, (2) interleaved pre-training, (3) speech-enhanced pre-training, and (4) comprehensive supervised fine-tuning on diverse textual, visual, and speech tasks. Our experimental results indicate that MIO exhibits competitive, and in some cases superior, performance compared to previous dual-modal baselines, any-to-any model baselines, and even modality-specific baselines. Moreover, MIO demonstrates advanced capabilities inherent to its any-to-any feature, such as interleaved video-text generation, chain-of-visual-thought reasoning, visual guideline generation, instructional image editing, etc.",
+  "Long-term memory is significant for agents, in which insights play a crucial role. However, the emergence of irrelevant insight and the lack of general insight can greatly undermine the effectiveness of insight. To solve this problem, in this paper, we introduce Multi-Scale Insight Agent (MSI-Agent), an embodied agent designed to improve LLMs' planning and decision-making ability by summarizing and utilizing insight effectively across different scales. MSI achieves this through the experience selector, insight generator, and insight selector. Leveraging a three-part pipeline, MSI can generate task-specific and high-level insight, store it in a database, and then use relevant insight from it to aid in decision-making. Our experiments show that MSI outperforms another insight strategy when planning by GPT3.5. Moreover, We delve into the strategies for selecting seed experience and insight, aiming to provide LLM with more useful and relevant insight for better decision-making. Our observations also indicate that MSI exhibits better robustness when facing domain-shifting scenarios."
 ]

doclens.0.json

@@ -1 +1 @@
-[206,104,226,67,200,185,221,212,206,222,88,210,228,174,155,205,172,218,148,132,212,91,163,184,205,132,213,190,212,198,230,227,159,198,122,216,175,197,118,217,219,224,69,220,197,72,204,92,169,191,191,155,175,111,218,77,207,36,195,178,123,170,231,91,209,177,146,205,151,221,217,95,199,89,153,216,154,202,167,213,104,184,176,226,200,232,53,223,73,202,220,158,174,189,165,222,158,221,211,78,205,72,214,212,215,232,175,219,110,205,192,226,34,176,209,158,222,132,179,208,98,126,205,126,172,167,227,100,224,182,208,117,217,199,195,191,169,178,158,217,152,157,163,163,204,209,146,217,150,194,217,23,125,200,221,200,212,41,176,223,207,95,178,232,68,182,173,205,198,210,139,152,147,215,196,223,83,199,123,197,119,230,223,65,216,85,210,52,210,204,179,111,138,215,83,177,219,69,212,77,182,226,99,178,207,197,87,190,222,216,85,208,211,66,220,226,221,134,175,190,170,166,157,216,135,211,132,200,67,227,195,178,221,179,205,168,186,208,127,207,139,205,67,209,223,117,195,190,202,64,218,77,199,221,189,125,216,80,148,214,143,181,98,221,194,112,219,212,138,216,87,127,187,219,122,220,97,223,221,164,205,220,100,227,101,171,188,223,89,213,137,175,172,219,77,102,234,109,197,114,205,184,221,138,175,152,163,133,227,73,224,181,174,147,144,178,147,224,211,121,123,211,219,209,210,204,80,182,215,152,118,224,216,154,220,163,204,187,133,151,162,221,94,184,224,213,72,187,148,223,195,110,182,117,224,88,202,162,220,154,151,197,227,197,74,221,205,97,221,219,103,206,184,72,191,201,192,230,164,217,170,214,118,221,218,118,215,181,224,78,183,154,190,206,102,202,74,195,96,225,228,221,99,224,104,123,203,184,211,90,209,173,199,203,99,201,176,160,207,132,231,96,195,213,173,101,190,206,61,225,232,215,178,211,227,192,148,195,213,114,212,127,162,214,213,129,220,70,176,224,209,137,232,116,228,212,75,182,207,71,111,173,189,207,96,172,213,119,222,93,195,204,211,76,179,200,184,216,107,135,202,71,118,219,123,202,210,146,225,76,227,62,214,226,98,158,202,219,169,83,156,223,125,211,213,102,219,223,72,224,178,190,204,110,228,64,214,200,193,205,213,160,201,216,134,195,128,186,213,219,187,199,216,84,202,150,211,127,230,206,204,180,183,183,167,213,224,72,209,79,195,205,153,228,133,203,210,78,190,207,195,133,225,192,197,190,201,187,222,109,138,227,103,223,209,164,190,73,226,200,205,191,189,100,226,135,198,129,185,207,229,148,209,216,58,222,117,219,92,221,147,222,219,63,216,228,165,181,157,213,197,218,158,191,186,223,204,109,172,229,91,231,204,102,192,217,204,144,222,173,209,209,95,186,195,60,212,219,209,162,183,227,216,111,193,182,222,71,183,222,122,178,219,130,228,82,225,223,69,198,232,63,193,207,216,139,223,74,164,198,224,80,148,227,138,227,199,225,86,148,230,169,210,92,166,187,202,165,196,78,202,74,229,173,216,215,213,164,205,102,206,91,212,173,198,109,183,94,206,115,224,126,229,222,57,225,191,221,218,215,44,177,217,214,218,191,221,80,198,109,196,95,192,181,214,214,123,208,191,225,219,218,108,204,150,199,206,90,227,71,207,123,199,106,131,213,93,178,208,60,132,217,149,204,80,227,218,202,94,232,175,213,115,217,114,222,200,173,184,217,222,178,226,205,192,185,197,180,193,205,211,136,221,62,184,213,89,225,71,169,216,135,198,98,214,204,88,191,154,207,213,227,93,230,133,216,189,122,224,108,229,237,218,209,214,66,153,203,219,204,222,218,107,174,214,148,169,188,210,98,203,142,167,174,224,103,223,220,148,216,199,188,175,173,130,156,97,220,111,216,115,216,70,221,210,77,173,162,216,164,216,69,203,175,172,166,199,156,184,131,201,210,98,220,133,211,116,221,82,213,88,213,128,227,219,177,190,216,180,237,217,64,215,134,221,172,220,221,70,169,221,189,226,74,229,197,209,128,190,213,106,221,198,162,184,182,219,86,201,143,229,205,146,228,106,154,209,60,216,222,74,221,215,141,168,202,82,194,213,80,217,214,204,164,199,220,149,114,140,215,150,218,108,109,211,170,206,125,183,148,193,229,210,124,188,143,160,153,199,178,75,225,105,199,83,222,112,205,75,222,205,70,104,194,91,158,220,99,215,209,219,65,124,215,158,223,234,208,101,218,200,66,188,222,149,201,189,211,51,179,208,198,160,182,152,195,141,216,112,205,207,170,128,219,118,188,223,224,80,177,218,127,196,151,159,117,186,113,216,212,134,204,90,200,231,184,222,68,146,151,158,202,173,144,206,171,215,68,188,222,89,215,117,223,80,191,209,204,105,228,67,174,210,74,208,105,151,159,183,142,163,202,214,41,147,222,227,188,208,200,157,132,195,94,191,185,214,132,201,155,166,195,220,147,219,156,214,165,220,105,223,217,100,176,225,117,207,134,166,202,218,172,200,157,183,217,87,214,181,229,217,76,231,199,139,154,213,208,208,169,218,82,219,191,139,207,222,49,122,154,176,219,110,185,112,137,231,80,208,136,189,192,208,190,192,187,180,220,186,225,218,208,102,190,124,152,83,219,199,95,198,133,235,214,96,213,217,148,168,200,32,145,207,222,198,171,208,218,104,178,230,77,214,129,218,136,139,212,233,93,221,153,221,95,155,151,211,225,60,81,217,201,108,208,234,172,177,172,193,208,72,216,224,211,44,205,82,221,224,199,198,221,137,208,81,183,105,182,106,222,180,184,146,180,205,187,192,163,219,213,164,229,218,190,147,221,193,213,182,126,228,231,97,173,218,116,161,156,207,122,193,198,155,207,103,223,192,92,153,223,170,206,177,225,40,224,106,203,208,116,203,105,197,152,221,211,84,226,111,215,154,224,221,65,215,142,169,212,184,135,207,85,209,213,76,225,229,130,203,217,186,229,140,177,116,216,219,62,209,105,164,150,207,214,211,114,148,230,118,201,134,197,124,209,163,184,164,186,189,219,106,221,220,95,141,217,87,200,224,114,220,168,212,112,229,192,106,189,183,209,212,85,187,202,219,222,223,223,212,226,79,193,128,222,209,206,197,178,152,114,222,111,164,183,189,179,214,130,149,150,212,122,160,195,118,115,204,144,163,159,140,211,208,120,222,220,125,195,174,220,80,173,204,87,149,212,82,221,119,213,139,186,227,97,215,213,136,215,68,229,218,63,224,182,221,218,94,213,90,168,202,85,168,222,121,215,213,93,221,83,220,112,197,213,213,92,210,76,216,79,179,220,94,194,99,186,181,197,214,194,138,221,91,218,172,159,219,74,153,221,201,108,213,131,217,112,214,107,209,35,224,188,219,108,191,105,157,211,126,206,148,220,126,217,164,203,129,201,211,119,204,165,209,75,205,130,204,215,206,119,178,211,218,137,193,167,199,220,182,115,207,184,189,217,178,186,159,208,230,140,194,75,173,205,64,213,167,189,110,220,195,136,137,196,134,208,120,198,182,189,176,162,183,172,172,214,200,95,212,189,193,184,195,116,167,199,110,180,217,126,193,226,142,204,66,140,222,226,218,144,218,214,140,206,66,196,224,143,121,166,221,101,154,204,216,201,221,152,225,69,226,226,180,200,181,212,128,193,206,136,219,141,208,128,202,209,105,168,178,204,211,110,145,163,193,211,69,220,147,194,223,165,212,218,124,197,229,226,132,220,156,211,80,203,140,192,94,208,102,180,215,134,152,218,106,191,204,102,211,108,182,204,206,208,90,165,197,105,186,115,213,208,186,165,186,174,213,211,164,210,62,129,201,217,170,169,217,193,167,222,174,217,167,128,182,113,159,208,85,172,219,89,219,126,218,190,65,227,208,52,225,125,160,205,135,168,186,213,212,69,124,205,67,204,110,151,180,220,205,193,106,223,80,124,166,218,194,138,148,205,88,179,183,163,227,221,198,213,87,190,200,239,81,202,211,213,115,204,105,216,83,170,201,210,95,219,219,180,216,222,228,86,231,83,227,116,223,84,207,216,115,204,109,194,171,198,183,197,86,216,144,209,125,226,221,57,215,117,199,185,152,230,174,220,61,209,99,163,218,218,134,183,212,85,208,92,190,214,81,146,220,181,224,214,212,79,171,209,217,209,100,213,72,220,223,193,72,130,203,111,214,192,197,222,201,229,204,189,162,124,221,157,218,34,204,88,170,205,76,168,210,46,196,223,73,180,85,118,200,85,221,68,160,202,201,219,181,148,207,210,208,69,210,101,215,76,217,104,188,180,224,71,199,166,203,106,216,196,182,84,183,125,128,224,89,206,88,212,212,152,205,92,210,65,166,171,200,120,228,213,83,163,131,153,180,215,228,99,179,210,82,218,95,209,94,215,206,196,110,236,219,209,193,95,172,177,218,218,140,203,228,102,160,215,102,204,192,89,168,222,56,223,155,189,213,208,220,78,204,213,168,202,169,230,191,218,203,73,222,127,208,143,221,217,217,100,160,212,208,156,223,197,205,201,223,220,144,209,90,209,139,182,218,22,221,183,219,79,216,194,224,86,208,225,190,102,200,212,162,211,83,221,106,215,113,161,197,111,216,210,92,219,124,208,185,152,203,220,230,106,182,193,185,221,79,197,79,231,192,202,113,166,211,142,195,170,179,226,222,208,228,152,133,200,89,197,180,155,215,97,201,139,205,145,217,163,213,85,223,209,200,139,217,123,160,183,201,136,210,206,105,208,132,206,208,101,134,174,112,205,181,221,215,221,213,225,116,217,80,162,186,120,183,122,214,201,97,188,209,174,229,205,120,194,203,130,228,134,228,83,201,119,218,210,55,225,64,171,174,227,107,226,95,139,190,154,171,206,139,154,219,157,224,213,206,212,79,135,186,156,217,186,128,118,184,187,213,221,86,183,217,218,210,216,155,195,188,134,172,223,125,176,167,85,187,214,217,94,213,128,217,133,192,217,60,189,122,217,117,224,95,199,74,206,89,221,205,158,196,77,228,114,188,105,210,70,209,83,188,169,214,225,184,205,127,197,115,182,174,181,238,222,223,59,229,219,112,205,115,190,128,196,210,222,176,215,194,187,112,212,90,183,207,86,212,85,178,187,138,217,80,203,96,221,198,82,207,96,164,227,208,76,214,179,209,186,207,205,221,224,143,224,178,228,189,229,132,213,182,222,218,67,229,186,201,169,211,88,210,48,219,152,225,207,62,200,210,220,68,216,44,137,155,181,221,83,214,103,222,183,90,215,86,179,205,128,219,179,164,202,130,224,148,221,146,175,184,213,117,190,201,142,216,82,231,230,92,172,218,207,189,223,150,226,46,216,209,221,216,111,168,219,92,197,228,204,204,101,223,65,211,220,203,122,206,108,224,74,181,142,216,189,190,180,212,107,223,120,191,232,56,209,214,66,209,222,116,172,222,101,179,177,185,168,193,163,194,209,193,105,170,211,212,105,191,117,90,226,90,190,121,216,60,207,67,161,171,220,219,89,184,221,144,182,194,208,214,214,226,196,133,188,202,204,68,194,216,214,77,208,92,215,63,204,178,197,77,115,190,152,227,181,207,102,199,131,208,216,177,116,202,220,121,223,128,196,175,211,219,207,74,218,215,221,93,177,214,183,192,143,139,196,217,226,83,102,119,211,100,212,172,183,180,204,219,226,96,194,47,149,186,143,160,221,224,61,226,147,214,60,198,207,164,146,200,140,182,207,196,208,180,186,215,111,181,221,214,161,216,169,208,136,168,178,112,189,196,124,234,119,202,67,201,74,163,172,148,179,211,143,124,191,202,192,175,218,80,209,72,190,156,217,117,223,122,180,193,182,186,210,219,201,202,224,64,138,192,114,199,208,190,109,218,149,208,97,213,189,87,232,131,152,188,205,219,196,225,94,197,164,210,173,191,222,185,172,189,205,163,208,73,196,201,73,224,206,110,191,122,221,136,165,221,185,156,210,69,210,211,210,102,213,86,170,209,221,197,207,50,154,74,96,212,180,231,158,208,139,150,166,127,213,216,202,95,201,155,217,54,206,214,208,179,140,191,136,228,191,91,232,45,145,220,162,220,74,209,147,155,160,182,217,209,160,174,180,227,219,221,182,100,212,67,213,148,208,51,188,209,82,211,210,71,218,82,176,88,174,117,186,210,160,157,212,135,165,201,162,170,136,176,220,189,167,219,49,212,190,220,73,152,150,176,204,221,124,220,209,117,175,213,228,173,195,159,194,218,57,201,214,164,175,229,79,176,116,206,137,203,152,173,206,78,227,209,154,175,190,89,225,113,222,219,214,50,219,66,202,90,188,214,80,195,74,212,60,130,206,186,157,204,122,198,73,194,230,108,196,205,213,83,192,104,207,117,216,171,126,222,99,229,221,79,214,79,217,144,217,197,206,207,110,160,206,172,197,183,207,217,207,113,210,221,71,161,221,164,227,214,142,177,185,180,103,130,198,123,205,74,216,102,219,160,217,75,204,114,192,213,166,188,118,222,227,92,195,219,161,200,221,69,203,143,198,198,217,198,66,212,50,208,116,199,125,210,207,167,225,116,207,97,184,99,220,184,203,184,219,177,167,202,214,55,207,161,197,122,212,226,187,96,216,201,188,135,224,207,139,225,230,220,121,221,107,212,66,170,169,210,199,102,220,94,159,184,207,92,207,231,214,125,227,220,205,58,193,203,215,223,229,78,196,170,185,196,162,234,56,201,123,171,231,196,86,162,199,213,220,68,200,68,205,88,225,135,220,82,182,215,222,79,152,230,62,162,218,184,224,67,206,99,189,124,214,197,73,204,105,221,179,102,218,232,80,214,181,170,204,165,216,207,217,212,195,176,215,106,192,160,221,182,217,57,211,88,198,233,113,171,204,138,193,209,225,59,176,184,134,223,151,193,200,217,100,225,79,180,142,190,123,222,80,232,216,133,216,148,211,110,198,96,187,224,95,208,112,178,227,94,171,96,181,209,170,225,196,206,94,216,87,217,171,191,82,218,127,227,176,219,207,230,79,214,203,105,213,143,174,188,125,193,220,60,215,172,214,101,211,110,161,117,187,180,125,218,220,62,208,203,217,87,198,156,216,226,161,161,223,224,72,178,198,213,195,219,208,140,175,217,74,201,201,66,186,154,229,89,226,169,204,87,184,85,161,133,201,80,176,188,114,224,77,207,126,202,83,219,200,125,172,169,190,216,80,88,221,68,218,133,216,117,217,157,217,170,190,124,214,210,156,231,84,207,204,113,200,70,222,162,208,227,92,223,136,167,195,221,221,77,173,213,109,214,117,211,217,89,217,91,210,152,194,206,202,110,216,177,190,207,227,185,172,230,172,207,171,199,234,207,149,194,192,179,212,209,210,101,198,225,85,164,211,110,194,182,211,224,65,228,218,79,224,81,122,208,154,129,206,92,193,171,148,188,221,80,220,161,165,166,161,214,99,210,64,174,224,221,105,200,122,230,216,94,223,128,225,161,219,126,187,137,191,222,214,148,151,198,218,210,110,208,228,184,211,35,202,218,195,216,115,212,95,177,199,101,184,208,202,212,134,193,129,192,81,182,223,70,226,230,134,167,183,198,222,227,227,226,63,213,109,187,177,219,223,203,144,179,209,103,177,181,158,221,90,222,166,207,175,230,207,99,205,234,210,210,168,223,143,210,187,209,204,150,209,213,208,193,221,214,77,215,199,81,197,82,177,190,210,231,79,179,221,64,182,199,82,204,204,95,172,187,178,209,86,222,220,118,192,223,88,220,77,174,104,224,137,182,186,96,207,198,74,152,196,217,206,79,214,208,204,180,94,215,81,177,160,201,164,173,205,76,199,220,228,91,215,155,226,79,133,181,136,182,226,96,221,109,209,223,71,202,95,217,87,202,204,183,210,187,212,81,226,184,224,88,170,214,198,226,142,212,81,209,189,172,192,221,216,123,221,126,204,218,222,76,205,73,225,221,73,204,108,201,88,174,197,136,223,90,189,56,207,147,206,212,73,201,83,204,112,137,227,67,208,137,219,225,65,200,186,99,214,97,215,74,203,65,199,216,108,216,80,206,219,104,226,180,225,199,186,197,226,157,102,177,107,231,156,141,226,70,220,216,223,64,214,66,201,174,170,207,46,202,131,173,218,125,217,157,234,192,159,174,209,95,196,224,59,220,69,211,130,203,222,88,208,86,198,127,219,228,75,218,170,168,198,128,215,54,211,167,186,117,211,162,221,219,105,223,99,223,127,202,218,213,143,194,181,200,180,230,224,97,181,132,173,202,221,57,151,220,77,220,160,206,188,101,197,72,213,95,193,212,189,105,226,100,205,201,56,211,93,178,212,88,208,83,213,165,219,183,236,121,220,210,94,212,171,186,218,137,212,129,175,203,223,134,194,95,193,191,105,229,208,102,196,120,191,221,217,65,206,200,74,168,180,199,217,119,223,68,211,125,204,105,180,164,215,227,128,211,166,218,86,185,74,214,57,200,171,111,185,73,199,220,213,192,216,107,211,115,219,227,192,221,101,203,65,211,51,216,84,193,121,214,86,195,115,179,229,90,215,92,207,63,179,212,38,202,104,182,125,179,99,147,184,210,166,227,232,164,120,218,169,203,154,192,224,217,122,160,205,206,221,80,191,217,166,202,78,206,147,202,155,195,76,204,136,191,112,195,160,147,226,91,224,216,212,177,188,165,174,130,203,221,220,133,209,147,216,69,159,155,143,213,94,227,139,209,163,183,199,112,217,213,98,217,96,185,158,173,229,51,209,195,227,214,161,213,83,168,229,209,118,221,224,59,179,161,220,209,193,199,199,212,107,226,219,204,117,166,223,122,166,181,163,176,223,176,130,223,221,202,89,188,147,160,143,218,223,206,151,201,161,130,176,175,138,126,209,112,230,94,211,17,103,218,73,218,131,210,104,214,63,222,38,135,140,215,143,215,191,185,223,207,215,203,46,219,207,93,177,85,213,191,223,56,181,209,82,210,221,66,210,195,223,184,138,217,48,194,73,150,199,220,183,209,60,194,103,218,103,211,216,124,197,217,185,106,185,207,174,165,204,138,220,68,218,151,202,68,214,155,183,221,66,216,61,218,122,214,178,202,178,217,142,215,126,187,148,219,98,180,222,217,80,210,203,43,208,154,220,101,167,206,211,212,208,72,147,225,139,174,207,36,200,234,205,211,180,205,202,126,159,186,116,211,154,192,155,194,168,198,160,218,220,202,153,222,215,66,174,128,211,104,136,171,235,219,112,156,209,109,203,132,192,181,215,112,205,68,215,82,213,117,189,221,186,211,171,208,136,189,128,210,96,199,107,195,232,74,223,132,193,198,46,220,73,181,112,224,133,221,144,224,83,232,217,131,186,53,214,225,95,203,70,102,217,106,224,79,210,113,177,150,228,220,102,225,80,221,170,206,105,223,112,210,46,201,89,197,207,128,235,111,212,161,144,221,182,200,77,213,229,90,134,223,179,212,204,125,197,215,80,233,218,44,226,53,152,184,220,113,219,216,110,214,206,151,215,224,216,163,144,190,133,223,195,216,203,67,95,169,191,131,208,78,104,176,179,148,207,172,220,98,202,118,218,204,120,213,92,213,93,210,203,219,75,212,227,212,188,187,201,100,206,151,200,96,197,215,157,210,70,207,182,205,205,101,212,117,230,86,163,143,167,189,215,168,216,194,98,218,128,219,94,149,188,217,48,172,174,131,131,182,171,200,115,220,217,91,200,80,178,188,226,49,192,205,222,127,194,134,175,214,115,212,214,82,193,106,217,48,197,114,204,114,201,221,190,174,214,168,223,86,217,212,214,181,204,96,190,189,216,91,204,118,226,110,198,224,158,195,117,189,200,150,231,206,91,209,207,118,223,183,232,146,158,207,213,122,204,118,200,103,200,227,76,179,195,73,215,93,214,170,215,232,41,210,107,138,202,204,125,198,134,225,80,117,164,185,197,106,232,74,139,216,207,209,57,207,94,200,229,190,192,140,112,208,155,191,177,216,203,142,192,103,195,219,91,179,228,187,115,213,217,192,193,215,141,218,70,186,37,225,190,84,178,177,162,218,210,185,176,195,97,218,63,218,176,227,215,149,224,221,115,208,214,133,182,188,205,163,207,58,199,217,129,208,184,214,206,133,228,200,80,224,179,229,152,208,95,194,170,224,178,196,181,94,199,90,203,75,216,153,169,213,86,225,67,192,194,65,189,201,103,188,153,163,213,226,142,185,133,226,106,181,215,199,209,211,56,204,114,181,163,171,228,228,73,74,198,203,186,178,185,125,229,221,204,41,165,189,126,205,173,116,179,198,159,216,129,209,222,174,183,229,95,212,68,177,152,217,138,156,135,105,204,193,188,127,209,150,133,163,208,80,218,232,211,77,230,37,198,224,165,213,81,220,207,195,173,174,212,102,206,117,196,178,222,134,205,216,203,86,151,184,157,217,222,123,213,159,195,121,207,159,220,120,212,176,144,217,67,173,216,105,206,90,220,121,217,59,184,219,156,213,149,143,216,221,140,225,182,115,209,115,209,45,223,172,227,133,187,165,199,168,224,91,206,115,153,202,197,62,169,210,134,215,167,203,214,141,200,213,182,90,214,170,206,199,219,54,167,154,72,194,122,181,197,129,214,105,153,209,137,202,227,72,207,61,178,127,181,210,200,46,188,210,214,67,189,216,51,209,125,190,127,208,110,191,219,137,213,76,206,120,186,121,201,222,113,195,194,68,183,179,184,223,61,180,220,197,133,208,226,136,217,200,93,178,220,113,197,198,172,141,225,102,159,149,213,196,100,220,196,176,232,182,187,171,165,182,101,175,169,191,224,110,200,128,200,129,114,179,188,165,198,216,184,174,216,67,229,198,220,32,232,219,72,219,203,127,88,212,81,142,223,210,166,97,145,209,77,216,227,196,83,202,137,214,82,223,114,205,177,183,196,214,129,196,122,223,157,232,99,180,188,203,132,229,223,186,115,209,191,218,50,192,184,220,102,207,87,196,162,219,92,221,140,217,139,169,213,79,211,99,205,104,200,86,210,90,157,151,227,228,53,205,72,195,75,226,89,226,74,218,145,228,224,208,171,215,153,140,208,182,161,228,107,209,220,217,207,125,181,195,212,220,95,202,95,191,233,74,201,184,221,81,231,181,120,227,119,139,121,179,199,203,216,154,210,144,195,129,153,213,103,209,219,212,125,216,229,219,108,223,65,212,92,221,197,162,211,147,210,197,178,221,162,192,172,215,84,194,52,204,70,175,187,187,194,186,235,185,177,170,216,213,64,212,102,191,112,143,204,96,164,226,218,107,182,116,224,157,223,171,194,104,228,114,218,40,207,54,204,220,108,199,214,195,81,158,130,133,116,118,203,215,215,146,219,210,69,216,121,225,59,210,65,217,202,79,209,76,156,152,178,193,86,228,50,217,94,220,71,156,206,84,202,88,113,211,215,65,168,221,195,219,213,148,204,84,212,217,184,218,228,118,222,76,222,226,205,126,218,224,216,77,122,218,74,213,81,220,66,190,132,212,213,200,216,63,204,105,169,166,173,193,142,201,168,213,96,200,210,93,210,217,214,182,204,199,172,159,200,216,162,198,168,191,200,99,214,227,230,87,171,204,195,176,210,165,158,221,118,195,182,217,225,217,191,210,120,164,100,222,195,227,81,229,174,207,212,92,191,204,206,61,209,143,230,113,218,224,188,223,95,216,71,154,212,107,150,171,192,204,66,216,218,113,218,206,155,187,185,209,180,111,230,66,206,89,225,62,218,183,201,229,215,172,196,114,199,211,54,203,198,211,110,223,85,219,133,133,221,154,155,186,205,77,36,213,221,196,174,180,135,217,54,181,219,215,194,206,154,216,101,209,162,184,192,147,224,84,183,223,68,197,155,205,174,97,199,177,211,221,68,204,103]
+[206,104,226,67,200,185,221,212,206,222,88,210,228,174,155,205,172,218,148,132,212,91,163,184,205,132,213,190,212,198,230,227,159,198,122,216,175,197,118,217,219,224,69,220,197,72,204,92,169,191,191,155,175,111,218,77,207,36,195,178,123,170,231,91,209,177,146,205,151,221,217,95,199,89,153,216,154,202,167,213,104,184,176,226,200,232,53,223,73,202,220,158,174,189,165,222,158,221,211,78,205,72,214,212,215,232,175,219,110,205,192,226,34,176,209,158,222,132,179,208,98,126,205,126,172,167,227,100,224,182,208,117,217,199,195,191,169,178,158,217,152,157,163,163,204,209,146,217,150,194,217,23,125,200,221,200,212,41,176,223,207,95,178,232,68,182,173,205,198,210,139,152,147,215,196,223,83,199,123,197,119,230,223,65,216,85,210,52,210,204,179,111,138,215,83,177,219,69,212,77,182,226,99,178,207,197,87,190,222,216,85,208,211,66,220,226,221,134,175,190,170,166,157,216,135,211,132,200,67,227,195,178,221,179,205,168,186,208,127,207,139,205,67,209,223,117,195,190,202,64,218,77,199,221,189,125,216,80,148,214,143,181,98,221,194,112,219,212,138,216,87,127,187,219,122,220,97,223,221,164,205,220,100,227,101,171,188,223,89,213,137,175,172,219,77,102,234,109,197,114,205,184,221,138,175,152,163,133,227,73,224,181,174,147,144,178,147,224,211,121,123,211,219,209,210,204,80,182,215,152,118,224,216,154,220,163,204,187,133,151,162,221,94,184,224,213,72,187,148,223,195,110,182,117,224,88,202,162,220,154,151,197,227,197,74,221,205,97,221,219,103,206,184,72,191,201,192,230,164,217,170,214,118,221,218,118,215,181,224,78,183,154,190,206,102,202,74,195,96,225,228,221,99,224,104,123,203,184,211,90,209,173,199,203,99,201,176,160,207,132,231,96,195,213,173,101,190,206,61,225,232,215,178,211,227,192,148,195,213,114,212,127,162,214,213,129,220,70,176,224,209,137,232,116,228,212,75,182,207,71,111,173,189,207,96,172,213,119,222,93,195,204,211,76,179,200,184,216,107,135,202,71,118,219,123,202,210,146,225,76,227,62,214,226,98,158,202,219,169,83,156,223,125,211,213,102,219,223,72,224,178,190,204,110,228,64,214,200,193,205,213,160,201,216,134,195,128,186,213,219,187,199,216,84,202,150,211,127,230,206,204,180,183,183,167,213,224,72,209,79,195,205,153,228,133,203,210,78,190,207,195,133,225,192,197,190,201,187,222,109,138,227,103,223,209,164,190,73,226,200,205,191,189,100,226,135,198,129,185,207,229,148,209,216,58,222,117,219,92,221,147,222,219,63,216,228,165,181,157,213,197,218,158,191,186,223,204,109,172,229,91,231,204,102,192,217,204,144,222,173,209,209,95,186,195,60,212,219,209,162,183,227,216,111,193,182,222,71,183,222,122,178,219,130,228,82,225,223,69,198,232,63,193,207,216,139,223,74,164,198,224,80,148,227,138,227,199,225,86,148,230,169,210,92,166,187,202,165,196,78,202,74,229,173,216,215,213,164,205,102,206,91,212,173,198,109,183,94,206,115,224,126,229,222,57,225,191,221,218,215,44,177,217,214,218,191,221,80,198,109,196,95,192,181,214,214,123,208,191,225,219,218,108,204,150,199,206,90,227,71,207,123,199,106,131,213,93,178,208,60,132,217,149,204,80,227,218,202,94,232,175,213,115,217,114,222,200,173,184,217,222,178,226,205,192,185,197,180,193,205,211,136,221,62,184,213,89,225,71,169,216,135,198,98,214,204,88,191,154,207,213,227,93,230,133,216,189,122,224,108,229,237,218,209,214,66,153,203,219,204,222,218,107,174,214,148,169,188,210,98,203,142,167,174,224,103,223,220,148,216,199,188,175,173,130,156,97,220,111,216,115,216,70,221,210,77,173,162,216,164,216,69,203,175,172,166,199,156,184,131,201,210,98,220,133,211,116,221,82,213,88,213,128,227,219,177,190,216,180,237,217,64,215,134,221,172,220,221,70,169,221,189,226,74,229,197,209,128,190,213,106,221,198,162,184,182,219,86,201,143,229,205,146,228,106,154,209,60,216,222,74,221,215,141,168,202,82,194,213,80,217,214,204,164,199,220,149,114,140,215,150,218,108,109,211,170,206,125,183,148,193,229,210,124,188,143,160,153,199,178,75,225,105,199,83,222,112,205,75,222,205,70,104,194,91,158,220,99,215,209,219,65,124,215,158,223,234,208,101,218,200,66,188,222,149,201,189,211,51,179,208,198,160,182,152,195,141,216,112,205,207,170,128,219,118,188,223,224,80,177,218,127,196,151,159,117,186,113,216,212,134,204,90,200,231,184,222,68,146,151,158,202,173,144,206,171,215,68,188,222,89,215,117,223,80,191,209,204,105,228,67,174,210,74,208,105,151,159,183,142,163,202,214,41,147,222,227,188,208,200,157,132,195,94,191,185,214,132,201,155,166,195,220,147,219,156,214,165,220,105,223,217,100,176,225,117,207,134,166,202,218,172,200,157,183,217,87,214,181,229,217,76,231,199,139,154,213,208,208,169,218,82,219,191,139,207,222,49,122,154,176,219,110,185,112,137,231,80,208,136,189,192,208,190,192,187,180,220,186,225,218,208,102,190,124,152,83,219,199,95,198,133,235,214,96,213,217,148,168,200,32,145,207,222,198,171,208,218,104,178,230,77,214,129,218,136,139,212,233,93,221,153,221,95,155,151,211,225,60,81,217,201,108,208,234,172,177,172,193,208,72,216,224,211,44,205,82,221,224,199,198,221,137,208,81,183,105,182,106,222,180,184,146,180,205,187,192,163,219,213,164,229,218,190,147,221,193,213,182,126,228,231,97,173,218,116,161,156,207,122,193,198,155,207,103,223,192,92,153,223,170,206,177,225,40,224,106,203,208,116,203,105,197,152,221,211,84,226,111,215,154,224,221,65,215,142,169,212,184,135,207,85,209,213,76,225,229,130,203,217,186,229,140,177,116,216,219,62,209,105,164,150,207,214,211,114,148,230,118,201,134,197,124,209,163,184,164,186,189,219,106,221,220,95,141,217,87,200,224,114,220,168,212,112,229,192,106,189,183,209,212,85,187,202,219,222,223,223,212,226,79,193,128,222,209,206,197,178,152,114,222,111,164,183,189,179,214,130,149,150,212,122,160,195,118,115,204,144,163,159,140,211,208,120,222,220,125,195,174,220,80,173,204,87,149,212,82,221,119,213,139,186,227,97,215,213,136,215,68,229,218,63,224,182,221,218,94,213,90,168,202,85,168,222,121,215,213,93,221,83,220,112,197,213,213,92,210,76,216,79,179,220,94,194,99,186,181,197,214,194,138,221,91,218,172,159,219,74,153,221,201,108,213,131,217,112,214,107,209,35,224,188,219,108,191,105,157,211,126,206,148,220,126,217,164,203,129,201,211,119,204,165,209,75,205,130,204,215,206,119,178,211,218,137,193,167,199,220,182,115,207,184,189,217,178,186,159,208,230,140,194,75,173,205,64,213,167,189,110,220,195,136,137,196,134,208,120,198,182,189,176,162,183,172,172,214,200,95,212,189,193,184,195,116,167,199,110,180,217,126,193,226,142,204,66,140,222,226,218,144,218,214,140,206,66,196,224,143,121,166,221,101,154,204,216,201,221,152,225,69,226,226,180,200,181,212,128,193,206,136,219,141,208,128,202,209,105,168,178,204,211,110,145,163,193,211,69,220,147,194,223,165,212,218,124,197,229,226,132,220,156,211,80,203,140,192,94,208,102,180,215,134,152,218,106,191,204,102,211,108,182,204,206,208,90,165,197,105,186,115,213,208,186,165,186,174,213,211,164,210,62,129,201,217,170,169,217,193,167,222,174,217,167,128,182,113,159,208,85,172,219,89,219,126,218,190,65,227,208,52,225,125,160,205,135,168,186,213,212,69,124,205,67,204,110,151,180,220,205,193,106,223,80,124,166,218,194,138,148,205,88,179,183,163,227,221,198,213,87,190,200,239,81,202,211,213,115,204,105,216,83,170,201,210,95,219,219,180,216,222,228,86,231,83,227,116,223,84,207,216,115,204,109,194,171,198,183,197,86,216,144,209,125,226,221,57,215,117,199,185,152,230,174,220,61,209,99,163,218,218,134,183,212,85,208,92,190,214,81,146,220,181,224,214,212,79,171,209,217,209,100,213,72,220,223,193,72,130,203,111,214,192,197,222,201,229,204,189,162,124,221,157,218,34,204,88,170,205,76,168,210,46,196,223,73,180,85,118,200,85,221,68,160,202,201,219,181,148,207,210,208,69,210,101,215,76,217,104,188,180,224,71,199,166,203,106,216,196,182,84,183,125,128,224,89,206,88,212,212,152,205,92,210,65,166,171,200,120,228,213,83,163,131,153,180,215,228,99,179,210,82,218,95,209,94,215,206,196,110,236,219,209,193,95,172,177,218,218,140,203,228,102,160,215,102,204,192,89,168,222,56,223,155,189,213,208,220,78,204,213,168,202,169,230,191,218,203,73,222,127,208,143,221,217,217,100,160,212,208,156,223,197,205,201,223,220,144,209,90,209,139,182,218,22,221,183,219,79,216,194,224,86,208,225,190,102,200,212,162,211,83,221,106,215,113,161,197,111,216,210,92,219,124,208,185,152,203,220,230,106,182,193,185,221,79,197,79,231,192,202,113,166,211,142,195,170,179,226,222,208,228,152,133,200,89,197,180,155,215,97,201,139,205,145,217,163,213,85,223,209,200,139,217,123,160,183,201,136,210,206,105,208,132,206,208,101,134,174,112,205,181,221,215,221,213,225,116,217,80,162,186,120,183,122,214,201,97,188,209,174,229,205,120,194,203,130,228,134,228,83,201,119,218,210,55,225,64,171,174,227,107,226,95,139,190,154,171,206,139,154,219,157,224,213,206,212,79,135,186,156,217,186,128,118,184,187,213,221,86,183,217,218,210,216,155,195,188,134,172,223,125,176,167,85,187,214,217,94,213,128,217,133,192,217,60,189,122,217,117,224,95,199,74,206,89,221,205,158,196,77,228,114,188,105,210,70,209,83,188,169,214,225,184,205,127,197,115,182,174,181,238,222,223,59,229,219,112,205,115,190,128,196,210,222,176,215,194,187,112,212,90,183,207,86,212,85,178,187,138,217,80,203,96,221,198,82,207,96,164,227,208,76,214,179,209,186,207,205,221,224,143,224,178,228,189,229,132,213,182,222,218,67,229,186,201,169,211,88,210,48,219,152,225,207,62,200,210,220,68,216,44,137,155,181,221,83,214,103,222,183,90,215,86,179,205,128,219,179,164,202,130,224,148,221,146,175,184,213,117,190,201,142,216,82,231,230,92,172,218,207,189,223,150,226,46,216,209,221,216,111,168,219,92,197,228,204,204,101,223,65,211,220,203,122,206,108,224,74,181,142,216,189,190,180,212,107,223,120,191,232,56,209,214,66,209,222,116,172,222,101,179,177,185,168,193,163,194,209,193,105,170,211,212,105,191,117,90,226,90,190,121,216,60,207,67,161,171,220,219,89,184,221,144,182,194,208,214,214,226,196,133,188,202,204,68,194,216,214,77,208,92,215,63,204,178,197,77,115,190,152,227,181,207,102,199,131,208,216,177,116,202,220,121,223,128,196,175,211,219,207,74,218,215,221,93,177,214,183,192,143,139,196,217,226,83,102,119,211,100,212,172,183,180,204,219,226,96,194,47,149,186,143,160,221,224,61,226,147,214,60,198,207,164,146,200,140,182,207,196,208,180,186,215,111,181,221,214,161,216,169,208,136,168,178,112,189,196,124,234,119,202,67,201,74,163,172,148,179,211,143,124,191,202,192,175,218,80,209,72,190,156,217,117,223,122,180,193,182,186,210,219,201,202,224,64,138,192,114,199,208,190,109,218,149,208,97,213,189,87,232,131,152,188,205,219,196,225,94,197,164,210,173,191,222,185,172,189,205,163,208,73,196,201,73,224,206,110,191,122,221,136,165,221,185,156,210,69,210,211,210,102,213,86,170,209,221,197,207,50,154,74,96,212,180,231,158,208,139,150,166,127,213,216,202,95,201,155,217,54,206,214,208,179,140,191,136,228,191,91,232,45,145,220,162,220,74,209,147,155,160,182,217,209,160,174,180,227,219,221,182,100,212,67,213,148,208,51,188,209,82,211,210,71,218,82,176,88,174,117,186,210,160,157,212,135,165,201,162,170,136,176,220,189,167,219,49,212,190,220,73,152,150,176,204,221,124,220,209,117,175,213,228,173,195,159,194,218,57,201,214,164,175,229,79,176,116,206,137,203,152,173,206,78,227,209,154,175,190,89,225,113,222,219,214,50,219,66,202,90,188,214,80,195,74,212,60,130,206,186,157,204,122,198,73,194,230,108,196,205,213,83,192,104,207,117,216,171,126,222,99,229,221,79,214,79,217,144,217,197,206,207,110,160,206,172,197,183,207,217,207,113,210,221,71,161,221,164,227,214,142,177,185,180,103,130,198,123,205,74,216,102,219,160,217,75,204,114,192,213,166,188,118,222,227,92,195,219,161,200,221,69,203,143,198,198,217,198,66,212,50,208,116,199,125,210,207,167,225,116,207,97,184,99,220,184,203,184,219,177,167,202,214,55,207,161,197,122,212,226,187,96,216,201,188,135,224,207,139,225,230,220,121,221,107,212,66,170,169,210,199,102,220,94,159,184,207,92,207,231,214,125,227,220,205,58,193,203,215,223,229,78,196,170,185,196,162,234,56,201,123,171,231,196,86,162,199,213,220,68,200,68,205,88,225,135,220,82,182,215,222,79,152,230,62,162,218,184,224,67,206,99,189,124,214,197,73,204,105,221,179,102,218,232,80,214,181,170,204,165,216,207,217,212,195,176,215,106,192,160,221,182,217,57,211,88,198,233,113,171,204,138,193,209,225,59,176,184,134,223,151,193,200,217,100,225,79,180,142,190,123,222,80,232,216,133,216,148,211,110,198,96,187,224,95,208,112,178,227,94,171,96,181,209,170,225,196,206,94,216,87,217,171,191,82,218,127,227,176,219,207,230,79,214,203,105,213,143,174,188,125,193,220,60,215,172,214,101,211,110,161,117,187,180,125,218,220,62,208,203,217,87,198,156,216,226,161,161,223,224,72,178,198,213,195,219,208,140,175,217,74,201,201,66,186,154,229,89,226,169,204,87,184,85,161,133,201,80,176,188,114,224,77,207,126,202,83,219,200,125,172,169,190,216,80,88,221,68,218,133,216,117,217,157,217,170,190,124,214,210,156,231,84,207,204,113,200,70,222,162,208,227,92,223,136,167,195,221,221,77,173,213,109,214,117,211,217,89,217,91,210,152,194,206,202,110,216,177,190,207,227,185,172,230,172,207,171,199,234,207,149,194,192,179,212,209,210,101,198,225,85,164,211,110,194,182,211,224,65,228,218,79,224,81,122,208,154,129,206,92,193,171,148,188,221,80,220,161,165,166,161,214,99,210,64,174,224,221,105,200,122,230,216,94,223,128,225,161,219,126,187,137,191,222,214,148,151,198,218,210,110,208,228,184,211,35,202,218,195,216,115,212,95,177,199,101,184,208,202,212,134,193,129,192,81,182,223,70,226,230,134,167,183,198,222,227,227,226,63,213,109,187,177,219,223,203,144,179,209,103,177,181,158,221,90,222,166,207,175,230,207,99,205,234,210,210,168,223,143,210,187,209,204,150,209,213,208,193,221,214,77,215,199,81,197,82,177,190,210,231,79,179,221,64,182,199,82,204,204,95,172,187,178,209,86,222,220,118,192,223,88,220,77,174,104,224,137,182,186,96,207,198,74,152,196,217,206,79,214,208,204,180,94,215,81,177,160,201,164,173,205,76,199,220,228,91,215,155,226,79,133,181,136,182,226,96,221,109,209,223,71,202,95,217,87,202,204,183,210,187,212,81,226,184,224,88,170,214,198,226,142,212,81,209,189,172,192,221,216,123,221,126,204,218,222,76,205,73,225,221,73,204,108,201,88,174,197,136,223,90,189,56,207,147,206,212,73,201,83,204,112,137,227,67,208,137,219,225,65,200,186,99,214,97,215,74,203,65,199,216,108,216,80,206,219,104,226,180,225,199,186,197,226,157,102,177,107,231,156,141,226,70,220,216,223,64,214,66,201,174,170,207,46,202,131,173,218,125,217,157,234,192,159,174,209,95,196,224,59,220,69,211,130,203,222,88,208,86,198,127,219,228,75,218,170,168,198,128,215,54,211,167,186,117,211,162,221,219,105,223,99,223,127,202,218,213,143,194,181,200,180,230,224,97,181,132,173,202,221,57,151,220,77,220,160,206,188,101,197,72,213,95,193,212,189,105,226,100,205,201,56,211,93,178,212,88,208,83,213,165,219,183,236,121,220,210,94,212,171,186,218,137,212,129,175,203,223,134,194,95,193,191,105,229,208,102,196,120,191,221,217,65,206,200,74,168,180,199,217,119,223,68,211,125,204,105,180,164,215,227,128,211,166,218,86,185,74,214,57,200,171,111,185,73,199,220,213,192,216,107,211,115,219,227,192,221,101,203,65,211,51,216,84,193,121,214,86,195,115,179,229,90,215,92,207,63,179,212,38,202,104,182,125,179,99,147,184,210,166,227,232,164,120,218,169,203,154,192,224,217,122,160,205,206,221,80,191,217,166,202,78,206,147,202,155,195,76,204,136,191,112,195,160,147,226,91,224,216,212,177,188,165,174,130,203,221,220,133,209,147,216,69,159,155,143,213,94,227,139,209,163,183,199,112,217,213,98,217,96,185,158,173,229,51,209,195,227,214,161,213,83,168,229,209,118,221,224,59,179,161,220,209,193,199,199,212,107,226,219,204,117,166,223,122,166,181,163,176,223,176,130,223,221,202,89,188,147,160,143,218,223,206,151,201,161,130,176,175,138,126,209,112,230,94,211,17,103,218,73,218,131,210,104,214,63,222,38,135,140,215,143,215,191,185,223,207,215,203,46,219,207,93,177,85,213,191,223,56,181,209,82,210,221,66,210,195,223,184,138,217,48,194,73,150,199,220,183,209,60,194,103,218,103,211,216,124,197,217,185,106,185,207,174,165,204,138,220,68,218,151,202,68,214,155,183,221,66,216,61,218,122,214,178,202,178,217,142,215,126,187,148,219,98,180,222,217,80,210,203,43,208,154,220,101,167,206,211,212,208,72,147,225,139,174,207,36,200,234,205,211,180,205,202,126,159,186,116,211,154,192,155,194,168,198,160,218,220,202,153,222,215,66,174,128,211,104,136,171,235,219,112,156,209,109,203,132,192,181,215,112,205,68,215,82,213,117,189,221,186,211,171,208,136,189,128,210,96,199,107,195,232,74,223,132,193,198,46,220,73,181,112,224,133,221,144,224,83,232,217,131,186,53,214,225,95,203,70,102,217,106,224,79,210,113,177,150,228,220,102,225,80,221,170,206,105,223,112,210,46,201,89,197,207,128,235,111,212,161,144,221,182,200,77,213,229,90,134,223,179,212,204,125,197,215,80,233,218,44,226,53,152,184,220,113,219,216,110,214,206,151,215,224,216,163,144,190,133,223,195,216,203,67,95,169,191,131,208,78,104,176,179,148,207,172,220,98,202,118,218,204,120,213,92,213,93,210,203,219,75,212,227,212,188,187,201,100,206,151,200,96,197,215,157,210,70,207,182,205,205,101,212,117,230,86,163,143,167,189,215,168,216,194,98,218,128,219,94,149,188,217,48,172,174,131,131,182,171,200,115,220,217,91,200,80,178,188,226,49,192,205,222,127,194,134,175,214,115,212,214,82,193,106,217,48,197,114,204,114,201,221,190,174,214,168,223,86,217,212,214,181,204,96,190,189,216,91,204,118,226,110,198,224,158,195,117,189,200,150,231,206,91,209,207,118,223,183,232,146,158,207,213,122,204,118,200,103,200,227,76,179,195,73,215,93,214,170,215,232,41,210,107,138,202,204,125,198,134,225,80,117,164,185,197,106,232,74,139,216,207,209,57,207,94,200,229,190,192,140,112,208,155,191,177,216,203,142,192,103,195,219,91,179,228,187,115,213,217,192,193,215,141,218,70,186,37,225,190,84,178,177,162,218,210,185,176,195,97,218,63,218,176,227,215,149,224,221,115,208,214,133,182,188,205,163,207,58,199,217,129,208,184,214,206,133,228,200,80,224,179,229,152,208,95,194,170,224,178,196,181,94,199,90,203,75,216,153,169,213,86,225,67,192,194,65,189,201,103,188,153,163,213,226,142,185,133,226,106,181,215,199,209,211,56,204,114,181,163,171,228,228,73,74,198,203,186,178,185,125,229,221,204,41,165,189,126,205,173,116,179,198,159,216,129,209,222,174,183,229,95,212,68,177,152,217,138,156,135,105,204,193,188,127,209,150,133,163,208,80,218,232,211,77,230,37,198,224,165,213,81,220,207,195,173,174,212,102,206,117,196,178,222,134,205,216,203,86,151,184,157,217,222,123,213,159,195,121,207,159,220,120,212,176,144,217,67,173,216,105,206,90,220,121,217,59,184,219,156,213,149,143,216,221,140,225,182,115,209,115,209,45,223,172,227,133,187,165,199,168,224,91,206,115,153,202,197,62,169,210,134,215,167,203,214,141,200,213,182,90,214,170,206,199,219,54,167,154,72,194,122,181,197,129,214,105,153,209,137,202,227,72,207,61,178,127,181,210,200,46,188,210,214,67,189,216,51,209,125,190,127,208,110,191,219,137,213,76,206,120,186,121,201,222,113,195,194,68,183,179,184,223,61,180,220,197,133,208,226,136,217,200,93,178,220,113,197,198,172,141,225,102,159,149,213,196,100,220,196,176,232,182,187,171,165,182,101,175,169,191,224,110,200,128,200,129,114,179,188,165,198,216,184,174,216,67,229,198,220,32,232,219,72,219,203,127,88,212,81,142,223,210,166,97,145,209,77,216,227,196,83,202,137,214,82,223,114,205,177,183,196,214,129,196,122,223,157,232,99,180,188,203,132,229,223,186,115,209,191,218,50,192,184,220,102,207,87,196,162,219,92,221,140,217,139,169,213,79,211,99,205,104,200,86,210,90,157,151,227,228,53,205,72,195,75,226,89,226,74,218,145,228,224,208,171,215,153,140,208,182,161,228,107,209,220,217,207,125,181,195,212,220,95,202,95,191,233,74,201,184,221,81,231,181,120,227,119,139,121,179,199,203,216,154,210,144,195,129,153,213,103,209,219,212,125,216,229,219,108,223,65,212,92,221,197,162,211,147,210,197,178,221,162,192,172,215,84,194,52,204,70,175,187,187,194,186,235,185,177,170,216,213,64,212,102,191,112,143,204,96,164,226,218,107,182,116,224,157,223,171,194,104,228,114,218,40,207,54,204,220,108,199,214,195,81,158,130,133,116,118,203,215,215,146,219,210,69,216,121,225,59,210,65,217,202,79,209,76,156,152,178,193,86,228,50,217,94,220,71,156,206,84,202,88,113,211,215,65,168,221,195,219,213,148,204,84,212,217,184,218,228,118,222,76,222,226,205,126,218,224,216,77,122,218,74,213,81,220,66,190,132,212,213,200,216,63,204,105,169,166,173,193,142,201,168,213,96,200,210,93,210,217,214,182,204,199,172,159,200,216,162,198,168,191,200,99,214,227,230,87,171,204,195,176,210,165,158,221,118,195,182,217,225,217,191,210,120,164,100,222,195,227,81,229,174,207,212,92,191,204,206,61,209,143,230,113,218,224,188,223,95,216,71,154,212,107,150,171,192,204,66,216,218,113,218,206,155,187,185,209,180,111,230,66,206,89,225,62,218,183,201,229,215,172,196,114,199,211,54,203,198,211,110,223,85,219,133,133,221,154,155,186,205,77,36,213,221,196,174,180,135,217,54,181,219,215,194,206,154,216,101,209,162,184,192,147,224,84,183,223,68,197,155,205,174,97,199,177,211,221,68,204,103,221,163,203,109,186]

ivf.pid.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:6613c7ede1b1268a0aa81b4873c0ea2fdd7eb51be3fcae2322436cc5abfadf93
-size 2419928
+oid sha256:cf68e610290773e0ac667e56ac14814c68413eceefc27a378b7b3cf68341b545
+size 2413016

metadata.json

@@ -37,7 +37,7 @@
     "checkpoint":"colbert-ir/colbertv2.0",
     "triples":"/future/u/okhattab/root/unit/experiments/2021.10/downstream.distillation.round2.2_score/round2.nway6.cosine.ib/examples.64.json",
     "collection":[
-      "list with 5310 elements starting with...",
+      "list with 5315 elements starting with...",
       [
         "Driven by large-data pre-training, Segment Anything Model (SAM) has been demonstrated as a powerful and promptable framework, revolutionizing the segmentation models. Despite the generality, customizing SAM for specific visual concepts without man-powered prompting is under explored, e.g., automatically segmenting your pet dog in different images. In this paper, we propose a training-free Personalization approach for SAM, termed as PerSAM. Given only a single image with a reference mask, PerSAM first localizes the target concept by a location prior, and segments it within other images or videos via three techniques: target-guided attention, target-semantic prompting, and cascaded post-refinement. In this way, we effectively adapt SAM for private use without any training. To further alleviate the mask ambiguity, we present an efficient one-shot fine-tuning variant, PerSAM-F. Freezing the entire SAM, we introduce two learnable weights for multi-scale masks, only training 2 parameters within 10 seconds for improved performance. To demonstrate our efficacy, we construct a new segmentation dataset, PerSeg, for personalized evaluation, and test our methods on video object segmentation with competitive performance.",
         "Freezing the entire SAM, we introduce two learnable weights for multi-scale masks, only training 2 parameters within 10 seconds for improved performance. To demonstrate our efficacy, we construct a new segmentation dataset, PerSeg, for personalized evaluation, and test our methods on video object segmentation with competitive performance. Besides, our approach can also enhance DreamBooth to personalize Stable Diffusion for text-to-image generation, which discards the background disturbance for better target appearance learning. Code is released at https://github.com/ZrrSkywalker/Personalize-SAM",
@@ -50,7 +50,7 @@
     "root":".ragatouille/",
     "experiment":"colbert",
     "index_root":null,
-    "name":"2024-09/30/04.53.55",
+    "name":"2024-09/30/05.53.45",
     "rank":0,
     "nranks":1,
     "amp":true,
@@ -59,8 +59,8 @@
   },
   "num_chunks":1,
   "num_partitions":8192,
-  "num_embeddings":908968,
-  "avg_doclen":171.1804143126,
+  "num_embeddings":909850,
+  "avg_doclen":171.1853245532,
   "RAGatouille":{
     "index_config":{
       "index_type":"PLAID",

pid_docid_map.json

@@ -5308,5 +5308,10 @@
   "5306":"2409.14254",
   "5307":"2409.14254",
   "5308":"2409.14195",
-  "5309":"2409.14195"
+  "5309":"2409.14195",
+  "5310":"2409.17066",
+  "5311":"2409.17066",
+  "5312":"2409.17692",
+  "5313":"2409.17692",
+  "5314":"2409.16686"
 }

plan.json

@@ -37,7 +37,7 @@
         "checkpoint": "colbert-ir\/colbertv2.0",
         "triples": "\/future\/u\/okhattab\/root\/unit\/experiments\/2021.10\/downstream.distillation.round2.2_score\/round2.nway6.cosine.ib\/examples.64.json",
         "collection": [
-            "list with 5310 elements starting with...",
+            "list with 5315 elements starting with...",
             [
                 "Driven by large-data pre-training, Segment Anything Model (SAM) has been demonstrated as a powerful and promptable framework, revolutionizing the segmentation models. Despite the generality, customizing SAM for specific visual concepts without man-powered prompting is under explored, e.g., automatically segmenting your pet dog in different images. In this paper, we propose a training-free Personalization approach for SAM, termed as PerSAM. Given only a single image with a reference mask, PerSAM first localizes the target concept by a location prior, and segments it within other images or videos via three techniques: target-guided attention, target-semantic prompting, and cascaded post-refinement. In this way, we effectively adapt SAM for private use without any training. To further alleviate the mask ambiguity, we present an efficient one-shot fine-tuning variant, PerSAM-F. Freezing the entire SAM, we introduce two learnable weights for multi-scale masks, only training 2 parameters within 10 seconds for improved performance. To demonstrate our efficacy, we construct a new segmentation dataset, PerSeg, for personalized evaluation, and test our methods on video object segmentation with competitive performance.",
                 "Freezing the entire SAM, we introduce two learnable weights for multi-scale masks, only training 2 parameters within 10 seconds for improved performance. To demonstrate our efficacy, we construct a new segmentation dataset, PerSeg, for personalized evaluation, and test our methods on video object segmentation with competitive performance. Besides, our approach can also enhance DreamBooth to personalize Stable Diffusion for text-to-image generation, which discards the background disturbance for better target appearance learning. Code is released at https:\/\/github.com\/ZrrSkywalker\/Personalize-SAM",
@@ -50,7 +50,7 @@
         "root": ".ragatouille\/",
         "experiment": "colbert",
         "index_root": null,
-        "name": "2024-09\/30\/04.53.55",
+        "name": "2024-09\/30\/05.53.45",
         "rank": 0,
         "nranks": 1,
         "amp": true,
@@ -59,6 +59,6 @@
     },
     "num_chunks": 1,
     "num_partitions": 8192,
-    "num_embeddings_est": 908968.0297851562,
-    "avg_doclen_est": 171.180419921875
+    "num_embeddings_est": 909849.965133667,
+    "avg_doclen_est": 171.18531799316406
 }