metadata
license: mit
library_name: mlx
datasets:
- FractalAIResearch/Fathom-V0.4-SFT-Shortest-Chains
- FractalAIResearch/Fathom-V0.6-Iterative-Curriculum-Learning
base_model: FractalAIResearch/Fathom-R1-14B
pipeline_tag: text-generation
tags:
- mlx
mlx-community/Fathom-R1-14B-6bit
This model mlx-community/Fathom-R1-14B-6bit was converted to MLX format from FractalAIResearch/Fathom-R1-14B using mlx-lm version 0.25.0.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("mlx-community/Fathom-R1-14B-6bit")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)