Comments (4)
aws-taylor
commented on August 24, 2024
Hello @henghui-zhu-amazon,
Mistral is on our internal roadmap - we'll be adding a roadmap item to Github soon and will update this issue with a reference.
-Taylor
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gsnaws
commented on August 24, 2024
Beta support added in 2.16 release - https://awsdocs-neuron.readthedocs-hosted.com/en/latest/release-notes/index.html#latest-neuron-release
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jimburtoft
commented on August 24, 2024
Instructions on how to compile and use are available at https://huggingface.co/aws-neuron/Mistral-neuron
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aws-rhsoln
commented on August 24, 2024
Please check the support added in 2.16 release. Closing the ticket. PLease reopen if you still see the issue.
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Related Issues (20)
- Can't save/serialize any models except GPT2 HOT 4
- Compilation error on llama 7 B with batch size 8 HOT 4
- from_pretrained is broken after transformers made safetensor serialization default HOT 1
- LLaMA fails when the input token length is over 1790 tokens HOT 6
- Llama2 inference overhead time way too long HOT 6
- llama-2/codellama benchmark for inf2.xlarge HOT 4
- Mixtral Model support HOT 2
- Vicuna13B model support HOT 1
- Inf2 Modified Llama 2 Loading Issue HOT 11
- Skipping generation for useless tokens, and modiying cacheids HOT 3
- How to use generate() with inputs_embeds HOT 2
- Mixtral config issue -- not handling null well HOT 8
- Generate Llama 2 from Embeddings HOT 5
- Infering logits from `model.forward` for the entire batch instead of the last forward's output. HOT 6
- Support for MPT model HOT 1
- `stopping_criteria_list(input_ids, probs)` does not check for the correct sequence. HOT 4
- User feedback when compiling and reloading a large model HOT 1
- Issue while compiling Mistral 7B 0.2 Instruct HOT 5
- Backward compatibility with saved llama 2 compiled artifacts HOT 1
- NaN outputs when masking llama model inputs HOT 8
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