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README.md
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---
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language:
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- en
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pipeline_tag: text-generation
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inference: false
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tags:
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- facebook
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- meta
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- pytorch
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- mistral
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- inferentia2
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- neuron
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---
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# Neuronx model for [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)
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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 [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf).
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You can find detailed information about the base model on its [Model Card](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1).
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This model has been exported to the `neuron` format using specific `input_shapes` and `compiler` parameters detailed in the paragraphs below.
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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.
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## Usage on Amazon SageMaker
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_coming soon_
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## Usage with 🤗 `optimum-neuron`
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```python
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>>> from optimum.neuron import pipeline
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>>> p = pipeline('text-generation', 'aws-neuron/Mistral-7B-Instruct-v0.1-neuron-4x2048-24-cores')
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>>> p("My favorite place on earth is", max_new_tokens=64, do_sample=True, top_k=50)
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[{'generated_text': 'My favorite place on earth is the ocean. It is where I feel most
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at peace. I love to travel and see new places. I have a'}]
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```
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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.
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## Arguments passed during export
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**input_shapes**
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```json
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{
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"batch_size": 4,
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"sequence_length": 2048,
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}
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```
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**compiler_args**
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```json
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{
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"auto_cast_type": "bf16",
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"num_cores": 24,
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}
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```
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