Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use henryscheible/eval_rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/eval_rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/eval_rte")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/eval_rte") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/eval_rte", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from henryscheible/eval_rte: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/henryscheible/eval_rte/resolve/main/training_args.bin
- Command line
-
hf download hf://henryscheible/eval_rte/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/henryscheible/eval_rte/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 9cfc1d66144539754cc325b5fd68c42f5ae2cdc8991a5c1fd13cd5d1df37d052
- Size of remote file:
- 3.38 kB
- SHA256:
- e9b4675a7f039441cf3c61f6d85a9eb39c3b855cd3217538e11ac6951a517014
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