Instructions to use Ailiance-fr/devstral-llm-ops-bf16-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ailiance-fr/devstral-llm-ops-bf16-lora with PEFT:
Task type is invalid.
- MLX
How to use Ailiance-fr/devstral-llm-ops-bf16-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-llm-ops-bf16-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-llm-ops-bf16-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-llm-ops-bf16-lora" --prompt "Once upon a time"
- Atomic Chat
- Xet hash:
- 5f38d8a57d9e10762b69480045345bca966d871d5b61b72a7982235ebfc69f5c
- Size of remote file:
- 370 MB
- SHA256:
- 7ceeeb47227810a0aa02f6811ddb2b6feb679c62791c01b8b8773e22874d2a42
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