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---
license: mit
library_name: transformers
datasets:
- FractalAIResearch/Fathom-V0.4-SFT-Shortest-Chains
- FractalAIResearch/Fathom-V0.6-Iterative-Curriculum-Learning
base_model: FractalAIResearch/Fathom-R1-14B
tags:
- mlx
---
# cnfusion/Fathom-R1-14B-mlx-4Bit
The Model [cnfusion/Fathom-R1-14B-mlx-4Bit](https://huggingface.co/cnfusion/Fathom-R1-14B-mlx-4Bit) was converted to MLX format from [FractalAIResearch/Fathom-R1-14B](https://huggingface.co/FractalAIResearch/Fathom-R1-14B) using mlx-lm version **0.22.3**.
## Use with mlx
```bash
pip install mlx-lm
```
```python
from mlx_lm import load, generate
model, tokenizer = load("cnfusion/Fathom-R1-14B-mlx-4Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
```
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