Instructions to use huggingkot/DeepScaleR-1.5B-Preview-q4f32_1-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use huggingkot/DeepScaleR-1.5B-Preview-q4f32_1-MLC with MLC-LLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| license: mit | |
| library_name: mlc-llm | |
| tags: | |
| - mlc-llm | |
| - web-llm | |
| 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 | |
| This is a MLC [converted weight](https://llm.mlc.ai/docs/compilation/convert_weights.html) from [DeepScaleR-1.5B-Preview](https://huggingface.co/agentica-org/DeepScaleR-1.5B-Preview) model in MLC format `q4f32_1`. | |
| The model can be used for projects [MLC-LLM](https://github.com/mlc-ai/mlc-llm) and [WebLLM](https://github.com/mlc-ai/web-llm). |