Instructions to use TigerHatKth/content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TigerHatKth/content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TigerHatKth/content")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TigerHatKth/content") model = AutoModelForSequenceClassification.from_pretrained("TigerHatKth/content", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from TigerHatKth/content: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/TigerHatKth/content/resolve/main/training_args.bin
- Command line
-
hf download hf://TigerHatKth/content/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/TigerHatKth/content/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- a5b23284fbcc2953a7f06256414f61bf457aa2b1746e2b4457aec1da05cadd4d
- Size of remote file:
- 4.54 kB
- SHA256:
- 8665a6153f697566afd4138abe82ebde9bae158d4e1a064559fa29523df5029c
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