Instructions to use NLPclass/text_classification_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLPclass/text_classification_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NLPclass/text_classification_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NLPclass/text_classification_bert") model = AutoModelForSequenceClassification.from_pretrained("NLPclass/text_classification_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from NLPclass/text_classification_bert: direct link, hf CLI and curl.
- Browser
- Download file 651 MB
-
https://huggingface.co/NLPclass/text_classification_bert/resolve/main/model.safetensors
- Command line
-
hf download hf://NLPclass/text_classification_bert/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/NLPclass/text_classification_bert/resolve/main/model.safetensors
651 MB
- Xet hash:
- 90c44d67d062488af37de8dcf389f375cb6dd82649d3a5695262851ee2d3b153
- Size of remote file:
- 651 MB
- SHA256:
- 5fdd67f352cb1891f25c66c561c8618c56858bb1661281c6e518768175b1483b
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