Text Generation
MLX
Safetensors
mistral3
rotorquant
kv-cache-quantization
2-bit
weight-quantization
leanstral
lean4
formal-proofs
theorem-proving
quantized
apple-silicon
mistral
Mixture of Experts
Instructions to use majentik/Leanstral-RotorQuant-MLX-2bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use majentik/Leanstral-RotorQuant-MLX-2bit 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("majentik/Leanstral-RotorQuant-MLX-2bit") 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 majentik/Leanstral-RotorQuant-MLX-2bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "majentik/Leanstral-RotorQuant-MLX-2bit" --prompt "Once upon a time"
File size: 132 Bytes
b85864d | 1 2 3 4 5 6 7 8 | {
"bos_token_id": 1,
"eos_token_id": 2,
"max_length": 1048576,
"pad_token_id": 11,
"transformers_version": "5.3.0.dev0"
}
|