Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use XYZ123XYZ/test-trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use XYZ123XYZ/test-trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="XYZ123XYZ/test-trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("XYZ123XYZ/test-trainer") model = AutoModelForSequenceClassification.from_pretrained("XYZ123XYZ/test-trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from XYZ123XYZ/test-trainer: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/XYZ123XYZ/test-trainer/resolve/main/training_args.bin
- Command line
-
hf download hf://XYZ123XYZ/test-trainer/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/XYZ123XYZ/test-trainer/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- 42a699fe653a0a02eb716dab1d493f1f7d0fdeaba31ad3cd5e20532e72fb8cb6
- Size of remote file:
- 4.86 kB
- SHA256:
- 0597a881df7821316e7b0ff880eee45458f9c91c5dae8233d5040a246c9d8c34
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.