m-a-p/CodeFeedback-Filtered-Instruction
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How to use matteocap/dolphin-2.8-mistral-7b-v02-Q_8-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir dolphin-2.8-mistral-7b-v02-Q_8-mlx matteocap/dolphin-2.8-mistral-7b-v02-Q_8-mlx
This model was converted to MLX format from cognitivecomputations/dolphin-2.8-mistral-7b-v02 using mlx-lm version 0.5.0.
Refer to the original model card for more details on the model.
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx_community/dolphin-2.8-mistral-7b-v02-Q_8-mlx")
response = generate(model, tokenizer, prompt="hello", verbose=True)
Quantized
Base model
mistral-community/Mistral-7B-v0.2