Instructions to use Ailiance-fr/devstral-lua-upy-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ailiance-fr/devstral-lua-upy-lora with PEFT:
Task type is invalid.
- MLX
How to use Ailiance-fr/devstral-lua-upy-lora 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("Ailiance-fr/devstral-lua-upy-lora") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use Ailiance-fr/devstral-lua-upy-lora with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "Ailiance-fr/devstral-lua-upy-lora" --prompt "Once upon a time"
- Atomic Chat
Commit History
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docs: add base vs tuned bench comparison
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docs: add Benchmark / Training metrics section
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Refresh model card: license chain + DISCLOSURE bandeau v2
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Upload adapter config
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Upload devstral-lua-upy LoRA weights
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initial commit
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