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<img src="https://huggingface.co/HuggingFaceH4/zephyr-7b-alpha/resolve/main/thumbnail.png" alt="Zephyr Logo" width="800" style="margin-left:'auto' margin-right:'auto' display:'block'"/>

# Neuronx model for [Zephyr 7B β](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta)

This repository contains [**AWS Inferentia2**](https://aws.amazon.com/ec2/instance-types/inf2/) and [`neuronx`](https://awsdocs-neuron.readthedocs-hosted.com/en/latest/) compatible checkpoints for [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta).
You can find detailed information about the base model on its [Model Card](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta).

This model has been exported to the `neuron` format using specific `input_shapes` and `compiler` parameters detailed in the paragraphs below.

Please refer to the 🤗 `optimum-neuron` [documentation](https://huggingface.co/docs/optimum-neuron/main/en/guides/models#configuring-the-export-of-a-generative-model) for an explanation of these parameters.

## Usage on Amazon SageMaker

_coming soon_

## Usage with 🤗 `optimum-neuron`

```python
from optimum.neuron import pipeline

pipe = pipeline('text-generation', 'aws-neuron/zephyr-7b-seqlen-2048-bs-4-cores-2')
# We use the tokenizer's chat template to format each message - see https://huggingface.co/docs/transformers/main/en/chat_templating
messages = [
    {
        "role": "system",
        "content": "You are a friendly chatbot who always responds in the style of a pirate",
    },
    {"role": "user", "content": "How many helicopters can a human eat in one sitting?"},
]
prompt = pipe.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```

This repository contains tags specific to versions of `neuronx`. When using with 🤗 `optimum-neuron`, use the repo revision specific to the version of `neuronx` you are using, to load the right serialized checkpoints.

## Arguments passed during export

**input_shapes**

```json
{
  "batch_size": 4,
  "sequence_length": 2048,
}
```

**compiler_args**

```json
{
  "auto_cast_type": "fp16",
  "num_cores": 2,
}
```
{"language": ["en"], "license": "mit", "tags": ["generated_from_trainer"], "datasets": ["HuggingFaceH4/ultrachat_200k", "HuggingFaceH4/ultrafeedback_binarized"], "base_model": "mistralai/Mistral-7B-v0.1", "widget": [{"text": "<|system|>\nYou are a pirate chatbot who always responds with Arr!</s>\n<|user|>\nThere's a llama on my lawn, how can I get rid of him?</s>\n<|assistant|>\n", "output": {"text": "Arr! 'Tis a puzzlin' matter, me hearty! A llama on yer lawn be a rare sight, but I've got a plan that might help ye get rid of 'im. Ye'll need to gather some carrots and hay, and then lure the llama away with the promise of a tasty treat. Once he's gone, ye can clean up yer lawn and enjoy the peace and quiet once again. But beware, me hearty, for there may be more llamas where that one came from! Arr!"}}], "pipeline_tag": "text-generation", "model-index": [{"name": "zephyr-7b-beta", "results": [{"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AI2 Reasoning Challenge (25-Shot)", "type": "ai2_arc", "config": "ARC-Challenge", "split": "test", "args": {"num_few_shot": 25}}, "metrics": [{"type": "acc_norm", "value": 62.03071672354948, "name": "normalized accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "HellaSwag (10-Shot)", "type": "hellaswag", "split": "validation", "args": {"num_few_shot": 10}}, "metrics": [{"type": "acc_norm", "value": 84.35570603465445, "name": "normalized accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "Drop (3-Shot)", "type": "drop", "split": "validation", "args": {"num_few_shot": 3}}, "metrics": [{"type": "f1", "value": 9.66243708053691, "name": "f1 score"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "TruthfulQA (0-shot)", "type": "truthful_qa", "config": "multiple_choice", "split": "validation", "args": {"num_few_shot": 0}}, "metrics": [{"type": "mc2", "value": 57.44916942762855}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "GSM8k (5-shot)", "type": "gsm8k", "config": "main", "split": "test", "args": {"num_few_shot": 5}}, "metrics": [{"type": "acc", "value": 12.736921910538287, "name": "accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "MMLU (5-Shot)", "type": "cais/mmlu", "config": "all", "split": "test", "args": {"num_few_shot": 5}}, "metrics": [{"type": "acc", "value": 61.07, "name": "accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "Winogrande (5-shot)", "type": "winogrande", "config": "winogrande_xl", "split": "validation", "args": {"num_few_shot": 5}}, "metrics": [{"type": "acc", "value": 77.7426992896606, "name": "accuracy"}], "source": {"url": "https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=HuggingFaceH4/zephyr-7b-beta", "name": "Open LLM Leaderboard"}}, {"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "AlpacaEval", "type": "tatsu-lab/alpaca_eval"}, "metrics": [{"type": "unknown", "value": 0.906, "name": "win rate"}], "source": {"url": "https://tatsu-lab.github.io/alpaca_eval/"}}, {"task": {"type": "text-generation", "name": "Text Generation"}, "dataset": {"name": "MT-Bench", "type": "unknown"}, "metrics": [{"type": "unknown", "value": 7.34, "name": "score"}], "source": {"url": "https://huggingface.co/spaces/lmsys/mt-bench"}}]}]}
transformers mistral text-generation generated_from_trainer conversational en dataset:HuggingFaceH4/ultrachat_200k dataset:HuggingFaceH4/ultrafeedback_binarized base_model:mistralai/Mistral-7B-v0.1 license:mit model-index autotrain_compatible endpoints_compatible text-generation-inference region:us