Instructions to use QomSSLab/SubjectClassifier-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use QomSSLab/SubjectClassifier-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="QomSSLab/SubjectClassifier-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("QomSSLab/SubjectClassifier-v1") model = AutoModelForSequenceClassification.from_pretrained("QomSSLab/SubjectClassifier-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from QomSSLab/SubjectClassifier-v1: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/QomSSLab/SubjectClassifier-v1/resolve/main/model.safetensors
- Command line
-
hf download hf://QomSSLab/SubjectClassifier-v1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/QomSSLab/SubjectClassifier-v1/resolve/main/model.safetensors
2.24 GB
- Xet hash:
- 140e5085e71514fc5a94140ecae661a30211cb8cdde416058c4da1ce70b15ca7
- Size of remote file:
- 2.24 GB
- SHA256:
- 5bd2b2efe8357f57f1a1daefa6a0631bf39ed3fd303737a58cc7a4ef7fec0aa7
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