README.md

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
tags:
  - mlx
pipeline_tag: text-generation

mlx-community/Fathom-R1-14B-8bit

This model mlx-community/Fathom-R1-14B-8bit 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-8bit")

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)