| license: mit | |
| library_name: transformers | |
| datasets: | |
| - AI-MO/NuminaMath-CoT | |
| - KbsdJames/Omni-MATH | |
| - RUC-AIBOX/STILL-3-Preview-RL-Data | |
| - hendrycks/competition_math | |
| language: | |
| - en | |
| base_model: agentica-org/DeepScaleR-1.5B-Preview | |
| pipeline_tag: text-generation | |
| tags: | |
| - mlx | |
| # bobig/DeepScaleR-1.5B-Preview-Q8 | |
| The Model [bobig/DeepScaleR-1.5B-Preview-Q8](https://huggingface.co/bobig/DeepScaleR-1.5B-Preview-Q8) was | |
| converted to MLX format from [agentica-org/DeepScaleR-1.5B-Preview](https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview) | |
| using mlx-lm version **0.21.4**. | |
| ## Use with mlx | |
| ```bash | |
| pip install mlx-lm | |
| ``` | |
| ```python | |
| from mlx_lm import load, generate | |
| model, tokenizer = load("bobig/DeepScaleR-1.5B-Preview-Q8") | |
| 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) | |
| ``` | |