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+Smaug-Llama-3-70B-Instruct-32K-Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+library_name: transformers
+license: llama3
+datasets:
+- aqua_rat
+- microsoft/orca-math-word-problems-200k
+- m-a-p/CodeFeedback-Filtered-Instruction
+---
+
+# Smaug-Llama-3-70B-Instruct-32K
+
+### Built with Meta Llama 3
+
+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.
+
+Needle-In-A-Haystack (https://github.com/jzhang38/EasyContext) heatmap:
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64c14f6b02e1f8f67c73bd05/8Z5XgqrZXKcb2hmeTKTT6.png)
+
+### Model Description
+
+- **Developed by:** [Abacus.AI](https://abacus.ai)
+- **License:** https://llama.meta.com/llama3/license/
+- **Finetuned from model:** [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct).
+
+## How to use
+
+The prompt format is unchanged from Llama 3 70B Instruct.
+
+### Use with transformers
+
+See the snippet below for usage with Transformers:
+
+```python
+import transformers
+import torch
+
+model_id = "abacusai/Smaug-Llama-3-70B-Instruct"
+
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device_map="auto",
+)
+
+messages = [
+    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
+    {"role": "user", "content": "Who are you?"},
+]
+
+prompt = pipeline.tokenizer.apply_chat_template(
+		messages, 
+		tokenize=False, 
+		add_generation_prompt=True
+)
+
+terminators = [
+    pipeline.tokenizer.eos_token_id,
+    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = pipeline(
+    prompt,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+print(outputs[0]["generated_text"][len(prompt):])
+```
+
+
+## Evaluation
+
+### Arena-Hard
+
+### Arena-Hard
+
+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. 
+
+| Model | Score | 95% Confidence Interval | Average Tokens |
+| :---- | ---------: | ----------: | ------: |
+| GPT-4-Turbo-2024-04-09 | 82.6  | (-1.8, 1.6)  | 662 |
+| GPT-4o | 78.3  | (-2.4, 2.1)  | 685 |
+| Gemini-1.5-pro-latest | 72.1  | (-2.3, 2.2)  | 630 |
+| Claude-3-Opus-20240229 | 60.4  | (-3.3, 2.4)  | 541 |
+| **Smaug-Llama-3-70B-Instruct-32K** | 60.0  | (-2.6, 2.1)  | 844 |
+| Smaug-Llama-3-70B-Instruct | 56.7  | (-2.2, 2.6)  | 661 |
+| GPT-4-0314 | 50.0  | (-0.0, 0.0)  | 423 |
+| Claude-3-Sonnet-20240229 | 46.8  | (-2.1, 2.2)  | 552 |
+| Llama-3-70B-Instruct | 41.1  | (-2.5, 2.4)  | 583 |
+| GPT-4-0613 | 37.9  | (-2.2, 2.0)  | 354 |
+| Mistral-Large-2402 | 37.7 | (-1.9, 2.6)  | 400 |
+| Mixtral-8x22B-Instruct-v0.1 | 36.4  | (-2.7, 2.9)  | 430 |
+| Qwen1.5-72B-Chat | 36.1 | (-2.5, 2.2)  | 474 |
+| Command-R-Plus | 33.1 | (-2.1, 2.2)  | 541 |
+| Mistral-Medium | 31.9  | (-2.3, 2.4)  | 485 |
+| GPT-3.5-Turbo-0613 | 24.8 | (-1.6, 2.0)  | 401 |
+
+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.
+
+### OpenLLM Leaderboard Manual Evaluation
+
+| Model | ARC  | Hellaswag | MMLU | TruthfulQA | Winogrande | GSM8K* | Average |
+| :---- | ---: | ------:   | ---: | ---:       | ---:       | ---:   | ---:   |
+| Smaug-Llama-3-70B-Instruct-32K | 70.1 | TBA | TBA | 61.9 | 82.2 | TBA | TBA |
+| Llama-3-70B-Instruct | 71.4 | 85.7 | 80.0 | 61.8 | 82.9 | 91.1 | 78.8 |
+
+**GSM8K** The GSM8K numbers quoted here are computed using a recent release
+of the [LM Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness/).
+The commit used by the leaderboard has a significant issue that impacts models that
+tend to use `:` in their responses due to a bug in the stop word configuration for
+GSM8K. The issue is covered in more detail in this
+[GSM8K evaluation discussion](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard/discussions/770).
+The score for both Llama-3 and this model are significantly different when evaluated
+with the updated harness as the issue with stop words has been addressed.

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