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
File size: 629 Bytes
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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). |