Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use wgj0714/TC_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wgj0714/TC_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wgj0714/TC_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wgj0714/TC_model") model = AutoModelForSequenceClassification.from_pretrained("wgj0714/TC_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from wgj0714/TC_model: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/wgj0714/TC_model/resolve/main/training_args.bin
- Command line
-
hf download hf://wgj0714/TC_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/wgj0714/TC_model/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 09096ce4514f157afc5540cf76b94c8704867c9bfc29bb66954f01d6282142e2
- Size of remote file:
- 4.92 kB
- SHA256:
- e90983ae65463d95aa1c531fcf3d8914ecab9a1ebd81c85a01378bf2461d8d6c
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