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--- |
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inference: false |
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library_name: transformers |
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language: |
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- en |
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- fr |
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- de |
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- es |
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- it |
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- pt |
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- ja |
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- ko |
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- zh |
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- ar |
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- el |
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- fa |
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- pl |
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- id |
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- cs |
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- he |
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- hi |
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- nl |
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- ro |
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- ru |
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- tr |
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- uk |
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- vi |
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license: cc-by-nc-4.0 |
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extra_gated_prompt: "By submitting this form, you agree to the [License Agreement](https://cohere.com/c4ai-cc-by-nc-license) and acknowledge that the information you provide will be collected, used, and shared in accordance with Cohere’s [Privacy Policy]( https://cohere.com/privacy). You’ll receive email updates about C4AI and Cohere research, events, products and services. You can unsubscribe at any time." |
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extra_gated_fields: |
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Name: text |
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Affiliation: text |
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Country: country |
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I agree to use this model for non-commercial use ONLY: checkbox |
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--- |
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# Model Card for Aya Expanse 8B |
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<img src="aya-expanse-8B.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/> |
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**Aya Expanse 8B** is an open-weight research release of a model with highly advanced multilingual capabilities. It focuses on pairing a highly performant pre-trained [Command family](https://huggingface.co/CohereForAI/c4ai-command-r-plus) of models with the result of a year’s dedicated research from [Cohere For AI](https://cohere.for.ai/), including [data arbitrage](https://arxiv.org/abs/2408.14960), [multilingual preference training](https://arxiv.org/abs/2407.02552), [safety tuning](https://arxiv.org/abs/2406.18682), and [model merging](https://arxiv.org/abs/2410.10801). The result is a powerful multilingual large language model. |
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This model card corresponds to the 8-billion version of the Aya Expanse model. We also released an 32-billion version which you can find [here](https://huggingface.co/CohereForAI/aya-expanse-32B). |
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- Developed by: [Cohere For AI](https://cohere.for.ai/) |
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- Point of Contact: Cohere For AI: [cohere.for.ai](https://cohere.for.ai/) |
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- License: [CC-BY-NC](https://cohere.com/c4ai-cc-by-nc-license), requires also adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy) |
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- Model: Aya Expanse 8B |
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- Model Size: 8 billion parameters |
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### Supported Languages |
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We cover 23 languages: Arabic, Chinese (simplified & traditional), Czech, Dutch, English, French, German, Greek, Hebrew, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese. |
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### Try it: Aya Expanse in Action |
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Use the [Cohere playground](https://dashboard.cohere.com/playground/chat) or our [Hugging Face Space](https://huggingface.co/spaces/CohereForAI/aya_expanse) for interactive exploration. |
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### How to Use Aya Expanse |
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Install the transformers library and load Aya Expanse 8B as follows: |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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model_id = "CohereForAI/aya-expanse-8b" |
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tokenizer = AutoTokenizer.from_pretrained(model_id) |
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model = AutoModelForCausalLM.from_pretrained(model_id) |
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# Format the message with the chat template |
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messages = [{"role": "user", "content": "Anneme onu ne kadar sevdiğimi anlatan bir mektup yaz"}] |
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input_ids = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt") |
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## <BOS_TOKEN><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Anneme onu ne kadar sevdiğimi anlatan bir mektup yaz<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|> |
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gen_tokens = model.generate( |
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input_ids, |
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max_new_tokens=100, |
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do_sample=True, |
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temperature=0.3, |
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) |
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gen_text = tokenizer.decode(gen_tokens[0]) |
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print(gen_text) |
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``` |
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### Example Notebooks |
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**Fine-Tuning:** |
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- [Detailed Fine-Tuning Notebook](https://colab.research.google.com/drive/1ryPYXzqb7oIn2fchMLdCNSIH5KfyEtv4). |
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**Community-Contributed Use Cases:**: |
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The following notebooks contributed by *Cohere For AI Community* members show how Aya Expanse can be used for different use cases: |
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- [Mulitlingual Writing Assistant](https://colab.research.google.com/drive/1SRLWQ0HdYN_NbRMVVUHTDXb-LSMZWF60) |
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- [AyaMCooking](https://colab.research.google.com/drive/1-cnn4LXYoZ4ARBpnsjQM3sU7egOL_fLB?usp=sharing) |
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- [Multilingual Question-Answering System](https://colab.research.google.com/drive/1bbB8hzyzCJbfMVjsZPeh4yNEALJFGNQy?usp=sharing) |
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## Model Details |
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**Input**: Models input text only. |
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**Output**: Models generate text only. |
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**Model Architecture**: Aya Expanse 8B is an auto-regressive language model that uses an optimized transformer architecture. Post-training includes supervised finetuning, preference training, and model merging. |
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**Languages covered**: The model is particularly optimized for multilinguality and supports the following languages: Arabic, Chinese (simplified & traditional), Czech, Dutch, English, French, German, Greek, Hebrew, Hindi, Indonesian, Italian, Japanese, Korean, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Turkish, Ukrainian, and Vietnamese |
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**Context length**: 8K |
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For more details about how the model was trained, check out [our blogpost](https://huggingface.co/blog/aya-expanse). |
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### Evaluation |
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We evaluated Aya Expanse 8B against Gemma 2 9B, Llama 3.1 8B, Ministral 8B, and Qwen 2.5 7B using the `dolly_human_edited` subset from the [Aya Evaluation Suite dataset](https://huggingface.co/datasets/CohereForAI/aya_evaluation_suite) and m-ArenaHard, a dataset based on the [Arena-Hard-Auto dataset](https://huggingface.co/datasets/lmarena-ai/arena-hard-auto-v0.1) and translated to the 23 languages we support in Aya Expanse 8B. Win-rates were determined using gpt-4o-2024-08-06 as a judge. For a conservative benchmark, we report results from gpt-4o-2024-08-06, though gpt-4o-mini scores showed even stronger performance. |
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The m-ArenaHard dataset, used to evaluate Aya Expanse’s capabilities, is publicly available [here](https://huggingface.co/datasets/CohereForAI/m-ArenaHard). |
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<img src="winrates_marenahard_complete.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/> |
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<img src="winrates_dolly.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/> |
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<img src="winrates_by_lang.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/> |
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<img src="winrates_step_by_step.png" width="650" style="margin-left:'auto' margin-right:'auto' display:'block'"/> |
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### Model Card Contact |
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For errors or additional questions about details in this model card, contact [email protected]. |
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### Terms of Use |
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We hope that the release of this model will make community-based research efforts more accessible, by releasing the weights of a highly performant multilingual model to researchers all over the world. This model is governed by a [CC-BY-NC](https://cohere.com/c4ai-cc-by-nc-license) License with an acceptable use addendum, and also requires adhering to [C4AI's Acceptable Use Policy](https://docs.cohere.com/docs/c4ai-acceptable-use-policy). |
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