Integrate LLM class
#9462
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Integrate LLM class
#9462
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Codecov ReportAttention: Patch coverage is
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## master #9462 +/- ##
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- Coverage 88.25% 87.50% -0.75%
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LLM class
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Very cool :) Made some formatting changes, and inference method needed the bos_token_id to not crash. Please confirm :)
This was referenced Jul 7, 2024
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1. #9462 2. **->** #9480 3. #9481 4. #9167 --- breaking #9167 down further, focusing on G-retriever model this time --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Akihiro Nitta <[email protected]> Co-authored-by: rusty1s <[email protected]>
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1. #9462 2. #9480 3. **->** #9481 4. #9167 --- Breaking down PR #9167 further --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Akihiro Nitta <[email protected]> Co-authored-by: rusty1s <[email protected]>
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1. #9462 2. #9480 3. #9481 4. **->** #9167 --- repro: Latest NVIDIA PyG container + `git config --global credential.helper store; huggingface-cli login; cd /opt/pyg; pip uninstall -y torch-geometric; rm -rf pytorch_geometric; git clone -b gnn-llm-model-integration https://github.com/pyg-team/pytorch_geometric.git; cd /opt/pyg/pytorch_geometric; pip install .; pip install peft datasets transformers pcst_fast sentencepiece; python3 examples/llm_plus_gnn/g_retriever.py` old PR: #9154 note: pure cpu is 220x slower than pure GPU using a single Grace Hopper (for llama-7b) info: tried gemma, performs worse in all train/val/test metrics. most likely needs some tuning, will leave this as future work as part of the community sprint to try many LLM and GNN combos and tune them. Therefore keeping the default llama2 the new gemma-v2 is also much worse than llama2 --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Akihiro Nitta <[email protected]> Co-authored-by: rusty1s <[email protected]>
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LLMclass #9462nn.models.GRetriever#9480WebQSPDataset#9481breaking #9167 into subPRs