bert-emotion-classifier safetensors download | Hugging Bay

Q: 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

Q: 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.

Q: 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.

Q: 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.

Q: 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.

Q: 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.

logasanjeev

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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This Python snippet downloads the selected file. Running the model needs its own library and setup.

from urllib.request import urlretrieve

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

Other ways

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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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Compare your file’s SHA-256 with the recorded hash.

6 hosted of 17 listed

Hashes recorded. Date not recorded.

File	Size	SHA-256	Source	Download
Weights
`model.safetensors` Default	438 MB	`15d5181f…65a186b8` `15d5181ffac4011c167e05d79d0bb0a7eff28875a52dc5673eb65fab65a186b8`	Hosted	Download
`model.onnx`	438.3 MB	`50df8103…99799d0f` `50df8103f1100490223e193457d0c1e13371dc5893d511805baebe5a99799d0f`	Upstream only	File metadata
Tokenizer & config
`class_wise_f1_plot.png`	46 KB	—	Upstream only	File metadata
`class_wise_metrics.csv`	1.5 KB	—	Upstream only	File metadata
`config.json`	2.14 KB	`ca9ad10f…e654ce86` `ca9ad10f587bd2fc07910e10e0662d5ebf768a032c2586f192ae6054e654ce86`	Hosted	Download
`emotion_labels.json`	333 bytes	—	Upstream only	File metadata
`inference.py`	3.79 KB	—	Upstream only	File metadata
`onnx_inference.py`	3.8 KB	—	Upstream only	File metadata
`optimized_thresholds.json`	947 bytes	—	Upstream only	File metadata
`tokenizer_config.json`	1.27 KB	`7b082b48…171186a0` `7b082b48a08a0b5c5939d99472e33addce3d96202155e33f7928cecd171186a0`	Hosted	Download
`training_curves_plot.png`	55.3 KB	—	Upstream only	File metadata
`vocab.txt`	231.5 KB	—	Upstream only	File metadata
`special_tokens_map.json`	125 bytes	`b6d346be…76237ee3` `b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3`	Hosted	Download
`tokenizer.json`	711.4 KB	`d241a60d…1f9e5c66` `d241a60d5e8f04cc1b2b3e9ef7a4921b27bf526d9f6050ab90f9267a1f9e5c66`	Hosted	Download
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`LICENSE`	1.08 KB	`7f73d082…186611dc` `7f73d08257cf967b7535aaa804e7e86e7535713d487a711074472047186611dc`	Hosted	Download
`README.md`	15.8 KB	—	Upstream only	File metadata

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shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

Get-FileHash -LiteralPath 'model.safetensors' -Algorithm SHA256

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bert-emotion-classifier

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