Instructions to use introvoyz041/RetroDFM-R-8B-mlx-4Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use introvoyz041/RetroDFM-R-8B-mlx-4Bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("introvoyz041/RetroDFM-R-8B-mlx-4Bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use introvoyz041/RetroDFM-R-8B-mlx-4Bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "introvoyz041/RetroDFM-R-8B-mlx-4Bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "introvoyz041/RetroDFM-R-8B-mlx-4Bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "introvoyz041/RetroDFM-R-8B-mlx-4Bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
- Xet hash:
- ff37018ea67abe614297f613344b56a58119f1ae8c912a21f9129d72f789bdda
- Size of remote file:
- 17.2 MB
- SHA256:
- 0f9ef3ce6b7335b487156fa80d716b2468e760aacc250438c90d09f269f49523
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