Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use henryscheible/eval_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/eval_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/eval_sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/eval_sst2") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/eval_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from henryscheible/eval_sst2: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/henryscheible/eval_sst2/resolve/main/training_args.bin
- Command line
-
hf download hf://henryscheible/eval_sst2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/henryscheible/eval_sst2/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 0787f31bf9903d556a7002362d67168726485b29b99c4ba42fd8020a5c1a8eae
- Size of remote file:
- 3.38 kB
- SHA256:
- 2a6b67f3d526169052c6f72a8e078a23dcece6a8637cb77759e976e70706ce19
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