Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
text-embeddings-inference
Instructions to use henryscheible/eval_v3_stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/eval_v3_stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/eval_v3_stsb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/eval_v3_stsb") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/eval_v3_stsb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from henryscheible/eval_v3_stsb: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/henryscheible/eval_v3_stsb/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://henryscheible/eval_v3_stsb/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/henryscheible/eval_v3_stsb/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 55375d1ebc98e2023e931fcbf29ce8611ded215290caa8dd822a25435a25696e
- Size of remote file:
- 438 MB
- SHA256:
- 0ee6078f08c63a6b3a48f545f8919fa000ada86589e5dd79b1b9f2d41b5401c6
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