Comments (2)
Mixtral-8x7B-Instruct-v0.1-mlx is using an outdated model format that is no longer compatible with the current script. You would use the hf model mistralai/Mixtral-8x7B-Instruct-v0.1
directly, or if you prefer to do qlora fine-tuning, you can use mlx-community/Mixtral-8x7B-Instruct-v0.1-hf-4bit-mlx
instead.
from mlx-examples.
Also you need to use mlx-lm
for MOE models like Mixtral, here's the doc. The simple lora example does not support those models.
from mlx-examples.
Related Issues (20)
- unable to run mixtral HOT 7
- QUESTION FOR HELP: Parametric quantities for quantitative models HOT 3
- Support Linear and DARE TIES merge methods from mergekit
- Unable to build mlx_lm from source HOT 4
- mlx_lm.server OpenAI compatible endpoints HOT 2
- Error loading models from mlx-community on HF HOT 3
- Command buffer execution failed: Insufficient Memory While tying to fine tune using lora.py
- Instruct tuning for lora/finetune? HOT 7
- No example for generating using the adapters.npz HOT 5
- Mnist example run error HOT 12
- mlx_lm.lora need an option to set --eos-token HOT 7
- [mlx-lm] Add format option to saveweights
- The stable diffusion example encountered an error after being upgraded to version 0.4. HOT 4
- is a mlx_lm.train command feasible? HOT 1
- How to generate an answer without pre-defined length of tokens? HOT 2
- Starcoder2 Support HOT 8
- Error 'Received invalid kth 2along axis -1 for array with shape: (1,2)' when generate using mixtral model with MLX format 4 quantized. HOT 7
- Inferencing with adapter vs Inferencing with fused model HOT 3
- Running python -m mlx_lm.fuse - Resulting in this error: IndexError: list index out of range HOT 2
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from mlx-examples.