professor3333/protocolledger-scibert

AI model by professor3333

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The model extracts actions, materials, quantities, equipment and locations, conditions, and the directed relations between them, from English wet-lab protocol text. Its output is a set of suggested preparation-sheet entries, each linked to its source characters, which a reviewer confirms or corrects in the ProtocolLedger interface before export. The system never does this; downstream users should not either. and checked at load time, because the cased checkpoint ships no tokenizer config and would otherwise lowercase mM to mm. sign in µL, which SciBERT maps to [UNK]) are substituted only in the text handed to the encoder. Offsets always refer to the original text. hash and the selection-report hash are all recorded in the bundle's bundle.json. The bundle was rebuilt on CPU and reproduces the GPU dev scores exactly (entity F1 0.8003, relation F1 0.6389). The released WNUT-2020 splits were the starting point, with these changes: document, always keeping the copy…

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Model overview

professor3333/protocolledger-scibert is a task-unspecified model repository published by professor3333 on Hugging Face. The source reports the pytorch library.

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Model facts

Task: Not reported
Library: pytorch
Recent downloads (30 days): 0
Cumulative likes: 0
Hugging Face trending score: 0
Reported safetensors parameters: 110,004,098
Architecture: Not reported
License: apache-2.0
Access: Not gated by Hugging Face
Created: 2026-10-11T06:09:09.000Z
Last modified: 2026-10-11T06:10:02.000Z

Compatibility and lineage

Reported languages: en

Reported base models: allenai/scibert_scivocab_cased

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Source: Hugging Face Hub. Metadata observed 2026-10-11T06:41:09.807Z. Daily imports are snapshots, not real-time monitoring.

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