Instructions to use Ailiance-fr/devstral-rust-embedded-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ailiance-fr/devstral-rust-embedded-lora with PEFT:
Task type is invalid.
- MLX
How to use Ailiance-fr/devstral-rust-embedded-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-rust-embedded-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-rust-embedded-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-rust-embedded-lora" --prompt "Once upon a time"
- Atomic Chat
Commit History
-
docs: add base vs tuned bench comparison
Verified signature30aea1b -
docs: add Benchmark / Training metrics section
Verified signature3d18790 -
Refresh model card: license chain + DISCLOSURE bandeau v2
Verified signaturec20ffe0 -
Upload adapter config
Verified signature9a1a6d2 -
Upload devstral-rust-embedded LoRA weights
Verified signaturec33d697 -
initial commit
Verified signature49a5069