Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use henryscheible/eval_v2_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/eval_v2_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/eval_v2_sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/eval_v2_sst2") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/eval_v2_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from henryscheible/eval_v2_sst2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/henryscheible/eval_v2_sst2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://henryscheible/eval_v2_sst2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/henryscheible/eval_v2_sst2/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- e04ffce4429ba9f4f8cc57c9c6a160a390b5f90c228faf7d87df3b8f6b6a8bfc
- Size of remote file:
- 438 MB
- SHA256:
- b274880346162c391112b33376b3ecf8583125d151d400ab0e8769d0acaa0460
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