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--- |
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license: other |
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language: |
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- en |
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library_name: transformers |
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tags: |
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- RLHF |
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- Nexusflow |
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- Athene |
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- Chat Model |
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--- |
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# Athene-V2-Chat-72B: Rivaling GPT-4o across Benchmarks |
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<p align="center"> |
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<a href="https://huggingface.co/Nexusflow" target="_blank">Nexusflow HF</a> - <a href="https://discord.gg/HDSVmNAs3y" target="_blank">Nexusflow Discord</a> |
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</p> |
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We introduce Athene-V2-Chat-72B, an open-weights LLM that rivals GPT-4o across benchmarks. It is trained through RLHF based off Qwen-2.5-72B. |
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Athene-V2-Chat-72B excels in chat, math and coding. Its sister model, [Athene-V2-Agent-72B](https://huggingface.co/Nexusflow/Athene-V2-Chat), surpasses GPT-4o in complex function calling and agent applications. |
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Benchmark performance: |
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<p align="center" width="100%"> |
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<a><img src="benchmark.jpg" alt="Benchmark" style="width: 100%; min-width: 300px; display: block; margin: auto;"></a> |
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</p> |
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- **Developed by:** The Nexusflow Team |
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- **Model type:** Chat Model |
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- **Finetuned from model:** [Qwen 2.5 72B](https://huggingface.co/Qwen/Qwen2.5-72B-Instruct) |
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- **License**: [Nexusflow Research License](https://huggingface.co/Nexusflow/Athene-V2-Chat/blob/main/Nexusflow_Research_License.pdf) |
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- **Blog**: https://nexusflow.ai/blogs/athene-V2 |
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## Usage |
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Athene-V2-Chat uses the same chat template as Qwen 2.5 72B. Below is an example simple usage using the Transformers library. |
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```Python |
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import transformers |
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import torch |
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model_id = "Nexusflow/Athene-V2-Chat" |
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pipeline = transformers.pipeline( |
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"text-generation", |
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model=model_id, |
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model_kwargs={"torch_dtype": torch.bfloat16}, |
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device_map="auto", |
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) |
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messages = [ |
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{"role": "system", "content": "You are an Athene Noctura, you can only speak with owl sounds. Whoooo whooo."}, |
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{"role": "user", "content": "Whooo are you?"}, |
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] |
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terminators = [ |
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pipeline.tokenizer.eos_token_id, |
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pipeline.tokenizer.convert_tokens_to_ids("<|end_of_text|>") |
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] |
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outputs = pipeline( |
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messages, |
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max_new_tokens=256, |
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eos_token_id=terminators, |
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do_sample=True, |
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temperature=0.6, |
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top_p=0.9, |
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) |
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print(outputs[0]["generated_text"][-1]) |
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``` |
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We found that by adding system prompts that enforce the model to think step by step, the model can do even better in math and problems like counting `r`s in strawberry. For fairness consideration we **do not** include such system prompt during chat evaluation. |
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## Acknowledgment |
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We would like to thank the [LMSYS Organization](https://lmsys.org/) for their support of testing the model. We would like to thank Meta AI and the open source community for their efforts in providing the datasets and base models. |
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