Instructions to use mlx-community/Mistral-7B-Instruct-v0.2-4-bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Mistral-7B-Instruct-v0.2-4-bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/Mistral-7B-Instruct-v0.2-4-bit") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use mlx-community/Mistral-7B-Instruct-v0.2-4-bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "mlx-community/Mistral-7B-Instruct-v0.2-4-bit" --prompt "Once upon a time"
Update config.json (#4)
Browse files- Update config.json (625bae0744b0d21a0ad593612afda46c4ef96a54)
Co-authored-by: Marc Sun <marcsun13@users.noreply.huggingface.co>
- config.json +0 -1
config.json
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"hidden_dim": 14336,
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"n_heads": 32,
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"n_kv_heads": 8,
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"rope_theta": 1000000.0,
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"norm_eps": 1e-05,
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"vocab_size": 32000,
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"quantization": {
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"hidden_dim": 14336,
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"n_heads": 32,
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"n_kv_heads": 8,
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"norm_eps": 1e-05,
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"vocab_size": 32000,
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"quantization": {
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