Instructions to use junaid1993/Belief_BERT_MultiClass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junaid1993/Belief_BERT_MultiClass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="junaid1993/Belief_BERT_MultiClass")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("junaid1993/Belief_BERT_MultiClass") model = AutoModelForSequenceClassification.from_pretrained("junaid1993/Belief_BERT_MultiClass", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-500/optimizer.pt from junaid1993/Belief_BERT_MultiClass: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/junaid1993/Belief_BERT_MultiClass/resolve/main/checkpoint-500/optimizer.pt
- Command line
-
hf download hf://junaid1993/Belief_BERT_MultiClass/checkpoint-500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/junaid1993/Belief_BERT_MultiClass/resolve/main/checkpoint-500/optimizer.pt
536 MB
- Xet hash:
- 622f7f7e1410c83eaeee6e9af3f36bbb0af3d92fca7ba316cbd8d9472fdd75be
- Size of remote file:
- 536 MB
- SHA256:
- dd94c4914731915f9e0c2a48898327ee84f616c330e507194d0a59c7b378bfef
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