# google/electra-base-discriminator

This model is a self supervised text encoder discriminator that learns to distinguish real tokens from fake tokens. It can be fine tuned for classification, question answering, and sequence tagging tasks such as GLUE, SQuAD, and text chunking.

## Cite this

- Page: https://huggingbay.xyz/artifact/hf-model-google-electra-base-discriminator
- Citation: google/electra-base-discriminator. The Hugging Bay model record. https://huggingbay.xyz/artifact/hf-model-google-electra-base-discriminator (retrieved 2026-11-13).
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## Facts

- Type: LLM
- Task: general
- Framework: transformers
- License: apache-2.0: Permissive open license: commercial use, modification, and redistribution are permitted. (https://spdx.org/licenses/Apache-2.0.html)
- Source: https://huggingface.co/google/electra-base-discriminator
- Hosting: hosted (7 files)
- Files: 7 hosted of 10 listed
- File counts: "listed" is every file in the source repository; only hosted files download from Hugging Bay, and the download plan lists the files it selects for one download, so its count can differ.
- Hosted here: 7 hosted of 10 listed
- Full repo upstream: 1.76 GB
- Recommended file: 440.3 MB · pytorch_model.bin
- Download: https://huggingbay.xyz/api/artifacts/hf-model-google-electra-base-discriminator/download-plan (download plan: https://huggingbay.xyz/api/artifacts/hf-model-google-electra-base-discriminator/download-plan)
- Per-file SHA-256: available for 7 of 7 hosted files via https://huggingbay.xyz/api/artifacts/hf-model-google-electra-base-discriminator/files?limit=100
- Availability: Ready
- Downloadable: yes
- Run-ready: no (Hugging Bay has not certified a run path for this model; hosted bytes are downloadable and hash-checkable only)
- Peer-assisted fallbacks: 0 verified, 0 pending review
- Downloads: 40918577
- Stars: 218
- Card completeness: 83%

## Description

This model is a self supervised text encoder discriminator that learns to distinguish real tokens from fake tokens. It can be fine tuned for classification, question answering, and sequence tagging tasks such as GLUE, SQuAD, and text chunking.

## Model Card Facts

- Declared license: apache-2.0
- Pipeline: general
- Library: transformers
- Task categories: general
- Languages: en
- Paper ids: 1406.2661
- File hints: 10 upstream file samples

## Referenced Data

- Paper: 1406.2661

## File Hints

- .gitattributes
- README.md
- config.json
- flax_model.msgpack
- pytorch_model.bin
- rust_model.ot
- tf_model.h5
- tokenizer.json
- tokenizer_config.json
- vocab.txt

## Quality Checklist

- Summary: passed
- Description: passed
- Model card metadata: passed
- License: passed
- Provenance: passed
- File inventory: passed
- Hosted bytes: passed
- Scan result: passed
- Manifest signature: passed

## Safety Notes

- Mirrored 1 selected Hugging Face file by configured-admin; hashes computed from downloaded bytes and manifest signed.
- External catalog metadata imported from Hugging Face public API on 2026-06-30T01:50:32.065Z.
- Open license detected as apache-2.0.
- Not a run kit: hosted, hash-checked bytes only; run readiness is not certified for this model yet.

## Actions

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