Text Generation
MLC-LLM
English
webllm
webgpu
browser
recursive-multi-agent
qwen2
latent
conversational
Instructions to use VishalMysore/RecursiveMAS-0.5B-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use VishalMysore/RecursiveMAS-0.5B-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
- Xet hash:
- d58befb82068dd8dc4df0718ed9763ada1409090aaf5e5804955e3ec5cbf2f84
- Size of remote file:
- 3.89 MB
- SHA256:
- 34111f8afd7679d9352eb62f8109438411aa3fdd4044b2a679fea5e8fd1d76d6
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