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Parent(s):
66a0f33
add 5.0bpw
Browse files- README.md +32 -0
- config.json +41 -0
- generation_config.json +6 -0
- huggingface-metadata.txt +24 -0
- measurement.json +0 -0
- model.safetensors.index.json +1002 -0
- output-00001-of-00004.safetensors +3 -0
- output-00002-of-00004.safetensors +3 -0
- output-00003-of-00004.safetensors +3 -0
- output-00004-of-00004.safetensors +3 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -0
README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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---
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This is a 5.0 bpw exl2 quant of [Mixtral-8x7B-instruct-cosmopedia-japanese20k](https://huggingface.co/aixsatoshi/Mixtral-8x7B-instruct-cosmopedia-japanese20k) calibrated against [cosmopedia-japanese-20k](https://huggingface.co/datasets/aixsatoshi/cosmopedia-japanese-20k). Rhe `measurement.json` in the repo, for anyone interested in other quants.
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**モデル概要**
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Mixtral-8x7B-instruct-cosmopedia-japanese20k モデルは、優れた性能を認められている Mixtral-8x7B-instruct の日本語ドメインへの適応を目的として設計されました。Mixtralはその高い能力にも関わらず、英語と日本語の推論結果には顕著な差があり、日本語のパフォーマンスが遅れをとっています。私たちの目標は、Mixtral の高度な論理的推論能力を損なうことなく、このモデルを日本語に適応させることでした。
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**外部翻訳システムを利用したトレーニングと開発**
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適応戦略として、Mixtral の推論能力のコアを凝縮した cosmopedia データを外部の翻訳システムを通じて日本語に翻訳し、この日本語のcosmopediaデータを使用して Mixtral モデルの再トレーニングを行い、日本語ドメインへの適応を促しました。この外部翻訳を利用したドメイン適応の方法により、Mixtral の論理的推論能力を日本語のコンテキストにシームレスに移行させ、モデルが意図した設計に沿った日本語でのパフォーマンスを実現しました。
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**改善点**
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Mixtral-8x7B-instruct-cosmopedia-japanese20k モデルは、別の日本語言語モデル、calm2 でトレーニングされたモデルに比べて、出力品質が向上しています。これは、適応プロセスの効果を強調し、私たちのモデルが期待される英語版の洗練された論理力を日本語に転移させ、日本語で複雑な推論タスクを実行する能力が強化されたことを示しています。
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**制限事項**
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進歩にも関わらず、モデルは時折、日本語で不自然またはぎこちない出力を生成することがあります。これらの事例は少ないものの、翻訳とドメイン適応技術を通じて完璧な言語的・文化的適応を達成することの課題を示しています。私たちは、このような出現を最小限に抑え、日本語出力の自然さと正確さをさらに向上させるために、モデルの洗練に取り組み続けています。
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**結論**
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Mixtral-8x7B-instruct-cosmopedia-japanese20k は、AI モデルにおける言語間のパフォーマンスギャップを埋めるための大きな一歩を表しています。日本語のような非英語言語が、先進的な AI の推理と推論能力を活用することが目標です。本モデルは実験モデルですが日本語での論理的推論が必要なアプリケーションに適しています。パフォーマンスと信頼性をさらに向上させるために、その制限を克服する必要があります。
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**Model Overview**
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The Mixtral-8x7B-instruct-cosmopedia-japanese20k model is engineered for the Japanese domain adaptation of the Mixtral-8x7B-instruct, a model recognized for its exceptional performance. Despite its proficiency, there is a noticeable disparity in inference outcomes between English and Japanese, with Japanese performance lagging. Our objective was to adapt this model to Japanese without compromising Mixtral’s advanced logical reasoning capabilities.
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**Training and Development**
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Our adaptation strategy involved leveraging cosmopedia data, which encapsulates the essence of Mixtral's reasoning prowess, translated into Japanese via an external translation system. This Japanese cosmopedia data was then used to retrain the Mixtral model, facilitating its domain adaptation to Japanese. This method of utilizing external translation for domain adaptation enabled us to seamlessly transpose Mixtral’s logical reasoning capabilities into a Japanese context, ensuring the model’s performance in Japanese matches its intended design.
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**Improvements**
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The Mixtral-8x7B-instruct-cosmopedia-japanese20k model exhibits significant output quality improvements over models trained with outputs from another Japanese language model, calm2. This highlights the effectiveness of our adaptation process and our model's enhanced ability to perform complex reasoning tasks in Japanese with the depth and sophistication expected of its English counterpart.
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**Limitations**
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Despite the advancements, the model occasionally produces outputs that may feel unnatural or awkward in Japanese. These instances, while fewer, point to the challenges of achieving perfect linguistic and cultural adaptation through translation and domain adaptation techniques. We continue to work on refining the model to minimize such occurrences and further improve the naturalness and accuracy of its Japanese language outputs.
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**Conclusion**
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The Mixtral-8x7B-instruct-cosmopedia-japanese20k marks a leap forward in bridging the language performance gap in AI models, enabling non-English languages, such as Japanese, to leverage advanced AI reasoning and inference capabilities. While particularly suited for applications requiring high-level logical reasoning in Japanese, we acknowledge the ongoing need to address its limitations to enhance performance and reliability further.
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config.json
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{
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"_name_or_path": "mistralai/Mixtral-8x7B-Instruct-v0.1",
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"architectures": [
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"MixtralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mixtral",
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"num_attention_heads": 32,
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"num_experts_per_tok": 2,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"num_local_experts": 8,
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"output_router_logits": false,
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"rms_norm_eps": 1e-05,
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"rope_theta": 1000000.0,
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"router_aux_loss_coef": 0.02,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.1",
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"use_cache": true,
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"vocab_size": 32000,
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"quantization_config": {
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"quant_method": "exl2",
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"version": "0.0.16",
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"bits": 5,
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"head_bits": 6,
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"calibration": {
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"rows": 100,
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"length": 2048,
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"dataset": "japanese_cosmo0000.parquet"
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}
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}
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"transformers_version": "4.38.1"
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}
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huggingface-metadata.txt
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url: https://huggingface.co/aixsatoshi/Mixtral-8x7B-instruct-cosmopedia-japanese20k
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branch: main
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download date: 2024-03-23 18:34:56
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sha256sum:
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dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055 tokenizer.model
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measurement.json
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model.safetensors.index.json
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|
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"bos_token": "<s>",
|
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"chat_template": "{{ bos_token }}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if message['role'] == 'user' %}{{ '[INST] ' + message['content'] + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ message['content'] + eos_token}}{% else %}{{ raise_exception('Only user and assistant roles are supported!') }}{% endif %}{% endfor %}",
|
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|
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|
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|
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|
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