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--- |
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library_name: transformers |
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license: llama3 |
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datasets: |
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- aqua_rat |
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- microsoft/orca-math-word-problems-200k |
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- m-a-p/CodeFeedback-Filtered-Instruction |
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--- |
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# Smaug-Llama-3-70B-Instruct-32K |
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### Built with Meta Llama 3 |
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This is a 32K version of Smaug-Llama-3-70B-Instruct. It uses PoSE (https://arxiv.org/abs/2309.10400) and LoRA (https://arxiv.org/abs/2106.09685) adapter transfer. More details are coming soon. |
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Needle-In-A-Haystack (https://github.com/jzhang38/EasyContext) heatmap: |
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### Model Description |
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- **Developed by:** [Abacus.AI](https://abacus.ai) |
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- **License:** https://llama.meta.com/llama3/license/ |
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- **Finetuned from model:** [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct). |
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## How to use |
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The prompt format is unchanged from Llama 3 70B Instruct. |
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### Use with transformers |
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See the snippet below for usage with Transformers: |
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```python |
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import transformers |
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import torch |
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model_id = "abacusai/Smaug-Llama-3-70B-Instruct" |
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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 a pirate chatbot who always responds in pirate speak!"}, |
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{"role": "user", "content": "Who are you?"}, |
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] |
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prompt = pipeline.tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True |
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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("<|eot_id|>") |
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] |
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outputs = pipeline( |
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prompt, |
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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"][len(prompt):]) |
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``` |
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## Evaluation |
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### Arena-Hard |
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### Arena-Hard |
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Score vs selected others (sourced from: (https://lmsys.org/blog/2024-04-19-arena-hard/#full-leaderboard-with-gpt-4-turbo-as-judge)). GPT-4o and Gemini-1.5-pro-latest were missing from the original blob post, and we produced those numbers from a local run using the same methodology. |
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| Model | Score | 95% Confidence Interval | Average Tokens | |
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| :---- | ---------: | ----------: | ------: | |
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| GPT-4-Turbo-2024-04-09 | 82.6 | (-1.8, 1.6) | 662 | |
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| GPT-4o | 78.3 | (-2.4, 2.1) | 685 | |
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| Gemini-1.5-pro-latest | 72.1 | (-2.3, 2.2) | 630 | |
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| Claude-3-Opus-20240229 | 60.4 | (-3.3, 2.4) | 541 | |
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| **Smaug-Llama-3-70B-Instruct-32K** | 60.0 | (-2.6, 2.1) | 844 | |
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| Smaug-Llama-3-70B-Instruct | 56.7 | (-2.2, 2.6) | 661 | |
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| GPT-4-0314 | 50.0 | (-0.0, 0.0) | 423 | |
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| Claude-3-Sonnet-20240229 | 46.8 | (-2.1, 2.2) | 552 | |
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| Llama-3-70B-Instruct | 41.1 | (-2.5, 2.4) | 583 | |
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| GPT-4-0613 | 37.9 | (-2.2, 2.0) | 354 | |
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| Mistral-Large-2402 | 37.7 | (-1.9, 2.6) | 400 | |
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| Mixtral-8x22B-Instruct-v0.1 | 36.4 | (-2.7, 2.9) | 430 | |
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| Qwen1.5-72B-Chat | 36.1 | (-2.5, 2.2) | 474 | |
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| Command-R-Plus | 33.1 | (-2.1, 2.2) | 541 | |
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| Mistral-Medium | 31.9 | (-2.3, 2.4) | 485 | |
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| GPT-3.5-Turbo-0613 | 24.8 | (-1.6, 2.0) | 401 | |
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Note that we believe the number of tokens/verbosity of the model strongly influences the GPT-4 judge in this case, and at least partially explains the improvement in Arena-Hard score for the 32K model. |
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### OpenLLM Leaderboard Manual Evaluation |
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| Model | ARC | Hellaswag | MMLU | TruthfulQA | Winogrande | GSM8K* | Average | |
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| :---- | ---: | ------: | ---: | ---: | ---: | ---: | ---: | |
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| Smaug-Llama-3-70B-Instruct-32K | 70.1 | TBA | TBA | 61.9 | 82.2 | TBA | TBA | |
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| Llama-3-70B-Instruct | 71.4 | 85.7 | 80.0 | 61.8 | 82.9 | 91.1 | 78.8 | |
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**GSM8K** The GSM8K numbers quoted here are computed using a recent release |
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of the [LM Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness/). |
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The commit used by the leaderboard has a significant issue that impacts models that |
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tend to use `:` in their responses due to a bug in the stop word configuration for |
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GSM8K. The issue is covered in more detail in this |
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[GSM8K evaluation discussion](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard/discussions/770). |
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The score for both Llama-3 and this model are significantly different when evaluated |
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with the updated harness as the issue with stop words has been addressed. |
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