Instructions to use quocvibui/rhino-coder-7b-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use quocvibui/rhino-coder-7b-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("quocvibui/rhino-coder-7b-lora") 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 quocvibui/rhino-coder-7b-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 "quocvibui/rhino-coder-7b-lora" --prompt "Once upon a time"
- Xet hash:
- 10691f49faeb7bbd564a7f96730f199b19df3e7ea3219c0033f33806b66b9ed6
- Size of remote file:
- 46.2 MB
- SHA256:
- ca9bbd859325ee8a1f5275affe10baed1d881338e500c512750bcc69f138a68f
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