Instructions to use owen99630/catexp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use owen99630/catexp2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="owen99630/catexp2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("owen99630/catexp2") model = AutoModelForSequenceClassification.from_pretrained("owen99630/catexp2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from owen99630/catexp2: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/owen99630/catexp2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://owen99630/catexp2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/owen99630/catexp2/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 9051aee10966eecb59f50dbe0b156e7f126a631deaf3998ae7ca5ef3fec4cfd5
- Size of remote file:
- 499 MB
- SHA256:
- ba7d8242631009c2f7db59f7d3f05640dd0cc4dc4f19c78a9204558ee5c270df
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