Instructions to use sabhashanki/text_classification-roberta_base_sept2022 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sabhashanki/text_classification-roberta_base_sept2022 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sabhashanki/text_classification-roberta_base_sept2022")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sabhashanki/text_classification-roberta_base_sept2022", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from sabhashanki/text_classification-roberta_base_sept2022: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/sabhashanki/text_classification-roberta_base_sept2022/resolve/main/tokenizer.json
- Command line
-
hf download hf://sabhashanki/text_classification-roberta_base_sept2022/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/sabhashanki/text_classification-roberta_base_sept2022/resolve/main/tokenizer.json
2.11 MB
- Xet hash:
- b3fbaa5e6535429c0f6a2e8fea0ffa6f48b8e7f80d2f7aaa6413073d50af4a74
- Size of remote file:
- 2.11 MB
- SHA256:
- ac296b52cd854626167142176554ffa73d0a4d2c837f41e14d9defba7b013b9b
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