Instructions to use CodeHima/TOSBert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CodeHima/TOSBert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CodeHima/TOSBert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CodeHima/TOSBert") model = AutoModelForSequenceClassification.from_pretrained("CodeHima/TOSBert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download mlb.joblib from CodeHima/TOSBert: direct link, hf CLI and curl.
- Browser
- Download file 724 Bytes
-
https://huggingface.co/CodeHima/TOSBert/resolve/main/mlb.joblib
- Command line
-
hf download hf://CodeHima/TOSBert/mlb.joblib
-
curl -L -o mlb.joblib https://huggingface.co/CodeHima/TOSBert/resolve/main/mlb.joblib
724 Bytes
- Xet hash:
- dd477ecc80f6d8a00f03b646581e4390a97f0f0c49372c70bdf7f36940794916
- Size of remote file:
- 724 Bytes
- SHA256:
- b7340bc560aa31dcfd956b79d1a2f337f95205fbc67eb42e5bd8e73318c5fb6b
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