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:
- d6c90147e3ab5c9ab2df2738484d68cab44f6becaa632f9fa5f5993e4a282192
- Size of remote file:
- 33 MB
- SHA256:
- 9d4da0fd3ff33d070c351bb33f041633c32ea0e4d49b9d31b96037b147324dfc
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