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:
- 60d8a8ff2db1fb6da449169b371cefce9ad7fc5f463184a5d69bde653db8f84f
- Size of remote file:
- 33.3 MB
- SHA256:
- 77c8c1f49b83d3d86112b281ae2326d386f6c7961882b7c1c236a8631867aa8c
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