Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use srmishra/crossencoder-stsb-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use srmishra/crossencoder-stsb-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="srmishra/crossencoder-stsb-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("srmishra/crossencoder-stsb-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("srmishra/crossencoder-stsb-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from srmishra/crossencoder-stsb-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/srmishra/crossencoder-stsb-roberta-base/resolve/main/training_args.bin
- Command line
-
hf download hf://srmishra/crossencoder-stsb-roberta-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/srmishra/crossencoder-stsb-roberta-base/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 22bba5e37a83200d31fcd3e89d1d0b55b191737fa62e5a30d9891cf92877d2ed
- Size of remote file:
- 4.6 kB
- SHA256:
- 2cec31b32d59f3fdc5ec94d7c4bbda58a9b877fd1a050128b1b722866d10622a
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