by facebookresearch · Agent Tool · ★ 1.3k
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Key functionality Choose your model, choose or add your prompt, run the inference. Browse contribution graph. Select the token to build the graph from. Tune the contribution threshold. Select representation of any token after any block. For the representation, see its projection to the output vocabulary, see which tokens were promoted/suppressed but the previous block. The following things are clickable: Edges. That shows more info about the contributing attention head. Heads when an edge is selected. You can see what this head is promoting/suppressing. FFN blocks (little squares on the graph). Neurons when an FFN block is selected. Installation Dockerized running Local Installation bash download git clone git@github.com:facebookresearch/llm-transparency-tool.git cd llm-transparency-tool install the necessary packages conda env create --name llmtt -f env.yaml install the package pip install -e . now, we need to build the
| Stars | 1,250 |
| Forks | 108 |
| Language | Python |
| Category | Agent Tool |
| Quality Score | 68.518457119272/100 |
| Open Issues | 9 |
| Last Updated | 2024-12-03 |
| Created | 2023-12-21 |
| Platforms | python |
| Est. Tokens | ~2k |
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llm-transparency-tool is LLM Transparency Tool (LLM-TT), an open-source interactive toolkit for analyzing internal workings of Transformer-based language models. *Check out demo at* https://huggingface.co/spaces/facebook/llm-. It is categorized as a Agent Tool with 1.3k GitHub stars.
llm-transparency-tool is primarily written in Python.
You can find installation instructions and usage details in the llm-transparency-tool GitHub repository at github.com/facebookresearch/llm-transparency-tool. The project has 1.3k stars and 108 forks, indicating an active community.
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