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.gitattributes

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README.md

@@ -0,0 +1,289 @@
+---
+language:
+- en
+- code
+license: apache-2.0
+tags:
+- merge
+- computer science
+- TensorBlock
+- GGUF
+datasets:
+- open-phi/programming_books_llama
+- open-phi/textbooks
+inference:
+  parameters:
+    do_sample: true
+    temperature: 0.2
+    top_p: 0.14
+    top_k: 12
+    max_new_tokens: 250
+    repetition_penalty: 1.15
+widget:
+- text: 'To calculate the factorial of n, we can use the following function:'
+base_model: Locutusque/TinyMistral-248M-v2.5
+model-index:
+- name: TinyMistral-248M-v2.5
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 24.57
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 27.49
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 23.15
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 46.72
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 47.83
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 0.0
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: IFEval (0-Shot)
+      type: HuggingFaceH4/ifeval
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: inst_level_strict_acc and prompt_level_strict_acc
+      value: 13.36
+      name: strict accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: BBH (3-Shot)
+      type: BBH
+      args:
+        num_few_shot: 3
+    metrics:
+    - type: acc_norm
+      value: 3.18
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MATH Lvl 5 (4-Shot)
+      type: hendrycks/competition_math
+      args:
+        num_few_shot: 4
+    metrics:
+    - type: exact_match
+      value: 0.0
+      name: exact match
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GPQA (0-shot)
+      type: Idavidrein/gpqa
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 0.11
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MuSR (0-shot)
+      type: TAUR-Lab/MuSR
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: acc_norm
+      value: 5.07
+      name: acc_norm
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU-PRO (5-shot)
+      type: TIGER-Lab/MMLU-Pro
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 1.5
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Locutusque/TinyMistral-248M-v2.5
+      name: Open LLM Leaderboard
+---
+
+<div style="width: auto; margin-left: auto; margin-right: auto">
+<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
+</div>
+<div style="display: flex; justify-content: space-between; width: 100%;">
+    <div style="display: flex; flex-direction: column; align-items: flex-start;">
+        <p style="margin-top: 0.5em; margin-bottom: 0em;">
+            Feedback and support: TensorBlock's  <a href="https://x.com/tensorblock_aoi">Twitter/X</a>, <a href="https://t.me/TensorBlock">Telegram Group</a> and <a href="https://x.com/tensorblock_aoi">Discord server</a>
+        </p>
+    </div>
+</div>
+
+## Locutusque/TinyMistral-248M-v2.5 - GGUF
+
+This repo contains GGUF format model files for [Locutusque/TinyMistral-248M-v2.5](https://huggingface.co/Locutusque/TinyMistral-248M-v2.5).
+
+The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b4242](https://github.com/ggerganov/llama.cpp/commit/a6744e43e80f4be6398fc7733a01642c846dce1d).
+
+<div style="text-align: left; margin: 20px 0;">
+    <a href="https://tensorblock.co/waitlist/client" style="display: inline-block; padding: 10px 20px; background-color: #007bff; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
+        Run them on the TensorBlock client using your local machine ↗
+    </a>
+</div>
+
+## Prompt template
+
+```
+
+```
+
+## Model file specification
+
+| Filename | Quant type | File Size | Description |
+| -------- | ---------- | --------- | ----------- |
+| [TinyMistral-248M-v2.5-Q2_K.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q2_K.gguf) | Q2_K | 0.105 GB | smallest, significant quality loss - not recommended for most purposes |
+| [TinyMistral-248M-v2.5-Q3_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q3_K_S.gguf) | Q3_K_S | 0.120 GB | very small, high quality loss |
+| [TinyMistral-248M-v2.5-Q3_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q3_K_M.gguf) | Q3_K_M | 0.129 GB | very small, high quality loss |
+| [TinyMistral-248M-v2.5-Q3_K_L.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q3_K_L.gguf) | Q3_K_L | 0.137 GB | small, substantial quality loss |
+| [TinyMistral-248M-v2.5-Q4_0.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q4_0.gguf) | Q4_0 | 0.149 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
+| [TinyMistral-248M-v2.5-Q4_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q4_K_S.gguf) | Q4_K_S | 0.149 GB | small, greater quality loss |
+| [TinyMistral-248M-v2.5-Q4_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q4_K_M.gguf) | Q4_K_M | 0.156 GB | medium, balanced quality - recommended |
+| [TinyMistral-248M-v2.5-Q5_0.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q5_0.gguf) | Q5_0 | 0.176 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
+| [TinyMistral-248M-v2.5-Q5_K_S.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q5_K_S.gguf) | Q5_K_S | 0.176 GB | large, low quality loss - recommended |
+| [TinyMistral-248M-v2.5-Q5_K_M.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q5_K_M.gguf) | Q5_K_M | 0.179 GB | large, very low quality loss - recommended |
+| [TinyMistral-248M-v2.5-Q6_K.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q6_K.gguf) | Q6_K | 0.204 GB | very large, extremely low quality loss |
+| [TinyMistral-248M-v2.5-Q8_0.gguf](https://huggingface.co/tensorblock/TinyMistral-248M-v2.5-GGUF/blob/main/TinyMistral-248M-v2.5-Q8_0.gguf) | Q8_0 | 0.264 GB | very large, extremely low quality loss - not recommended |
+
+
+## Downloading instruction
+
+### Command line
+
+Firstly, install Huggingface Client
+
+```shell
+pip install -U "huggingface_hub[cli]"
+```
+
+Then, downoad the individual model file the a local directory
+
+```shell
+huggingface-cli download tensorblock/TinyMistral-248M-v2.5-GGUF --include "TinyMistral-248M-v2.5-Q2_K.gguf" --local-dir MY_LOCAL_DIR
+```
+
+If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:
+
+```shell
+huggingface-cli download tensorblock/TinyMistral-248M-v2.5-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
+```

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