Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use henryscheible/sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/sst2") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from henryscheible/sst2: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/henryscheible/sst2/resolve/main/training_args.bin
- Command line
-
hf download hf://henryscheible/sst2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/henryscheible/sst2/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 02f304d827a9b842ce935d4fa3ee91fb0e8f029e3f82e9c27a85d728a39cd13a
- Size of remote file:
- 3.38 kB
- SHA256:
- 094322f04e7dccb84e8b19e17e83738c9294fe97dd8b285210980e96162e8166
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