Comments (7)
Yea it's a good point. Will look into updating the example to use the official weights instead of the ones from MixtralKit
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This one right? https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1
I'll test it after getting the official Mistral one working
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One major issue how to run it with 64 GB memory ? This is a huge model, we need to think of reducing the precision. Is it also possible to think of delta in the weights between the chat (instruction version Mixtral-8x7B-Instruct-v0.1) and the native generator (mixtral-8x7b-32kseqlen). But I don't see an easy way so far to run on M1 64 GB. running the convert give me a terminal killed message
(tf) tgg@gvalmu00008 mixtral % python convert.py --model_path mixtral-8x7b-32kseqlen/
zsh: killed python convert.py --model_path mixtral-8x7b-32kseqlen/
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I was able to use the llama.cpp convert script to get it to q4_0
and run in (M2, 96GB of RAM) -- I cannot with f16
seeing very weird output from the model though. will try to look into this more later, looking forward to learning/playing around w/ mlx on some of these models
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I'm able to get the someone13574 running.
I attempted the cat/convert process on the official instruct model, but no dice.
Is there a way to modify the convert script to get the instruct version going?
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That's the one.
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Related Issues (20)
- Llama-3-8B-Instruct-Gradient-1048k-4bit not working? HOT 2
- Generating after LORA training CAN NOT Stop Properly HOT 3
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- mlx 0.13 very slow with q8 and fp16 HOT 5
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- Phi-3-mini-4k-instruct : Failing to stop at <|end|> on generating the answer. HOT 5
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- [Feature Request] Function Calling for mlx_lm.server HOT 4
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