Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use reyj1999/test_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reyj1999/test_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reyj1999/test_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reyj1999/test_model") model = AutoModelForSequenceClassification.from_pretrained("reyj1999/test_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from reyj1999/test_model: direct link, hf CLI and curl.
- Browser
- Download file 4.47 kB
-
https://huggingface.co/reyj1999/test_model/resolve/main/training_args.bin
- Command line
-
hf download hf://reyj1999/test_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/reyj1999/test_model/resolve/main/training_args.bin
4.47 kB
- Xet hash:
- ea41e9532da3e9a908b57ac467bc6260d38268c4f2114e5e839f5ea7d7c19c1b
- Size of remote file:
- 4.47 kB
- SHA256:
- b8f7531dfd642f497224fb4ad51088f4698e90bc156a65504043660fb6d356ce
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