bert-emotion-classifier safetensors download | Hugging Bay

bert-emotion-classifier

logasanjeev/bert-emotion-classifier

Model details

text classificationLicense: mitSHA-256 recorded for 7 of 17 filesONNX · safetensors

Content controls: not assessed.

Listed for labeling text; for developers building text classifiers. Catalog sources: license, cardMetadata.license, task, cardMetadata.pipelineTag.

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from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-logasanjeev-bert-emotion-classifier/model.safetensors",
    "model.safetensors",
)

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6 hosted of 17 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors438 MB · 1 file Download · 438 MB (1 file)

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Datos del modelo

bert-emotion-classifier is an open-weights language model for text classification. The primary file is model.safetensors (438 MB). The primary file needs about 2 GB free for the selected file (file plus room to run it). License: MIT. The SHA-256 prefix is 15d5181ffac4. The primary Download is available now. No tested run commands for this file yet. See Files for current download availability. The size and hash details refer to the selected file, not every file in the repository. The memory figure is estimated from recorded file size with working room included.

Qué incluye

6 hosted of 17 listed

Weights

Tokenizer & config

README, LICENSE & .gitattributes

Acerca de este modelo

External Hugging Face catalog record for logasanjeev/bert-emotion-classifier. Task: text classification. Library: transformers. Languages: en. Datasets referenced by card metadata: google-research-datasets/go_emotions. Includes 12 model-card evaluation signals. Popularity signal at import: 1,754 downloads and 12 likes.

Datos básicos

Hosted here: 6 hosted of 17 listed
Full repo upstream: 877.4 MB
Recommended file: 438 MB · model.safetensors
Languages: en
Format: ONNX · safetensors
Downloads on Hugging Face: 2,125
File hashes: Hashes recorded. Date not recorded.

Licencia y origen

License: mit

6 hosted of 17 listed

Check the license text and keep the required notices when you use or share the files.

Upstream source →

See the JSON record →

License: MIT. Free to use and share, keep the credit notice
Task: text classification
Hosted here: at least 6 listed files; full count and size unknown
Full repo upstream: 877.4 MB
Recommended file: 438 MB · model.safetensors
Files: 6 hosted of 17 listed
Download: Download here (6 hosted files)
Added to Hugging Bay: Jun 30, 2026
Updated at source: Sep 22, 2026
Source: logasanjeev/bert-emotion-classifier

FAQ

What is this model?

logasanjeev/bert-emotion-classifier is an open-weights language model for text classification published by logasanjeev, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for text classification: logasanjeev/bert-emotion-classifier · transformers

Can I use it commercially?

It is released under the mit license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

How big is it?

Hosted here: at least 6 listed files; full count and size unknown. Full repo upstream: 877.4 MB. The recommended download, model.safetensors, is 438 MB.

What can I download here?

Hosted here: at least 6 listed files; full count and size unknown. Full repo upstream: 877.4 MB. The original release is at https://huggingface.co/logasanjeev/bert-emotion-classifier.

File checks and computer fit

File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 6 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-logasanjeev-bert-emotion-classifier/safety on Hugging Bay.

Will logasanjeev/bert-emotion-classifier run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.