Text Classification
Transformers
PyTorch
Safetensors
English
bert
stsb
glue
torchdistill
text-embeddings-inference
Instructions to use yoshitomo-matsubara/bert-large-uncased-stsb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yoshitomo-matsubara/bert-large-uncased-stsb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yoshitomo-matsubara/bert-large-uncased-stsb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yoshitomo-matsubara/bert-large-uncased-stsb") model = AutoModelForSequenceClassification.from_pretrained("yoshitomo-matsubara/bert-large-uncased-stsb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yoshitomo-matsubara/bert-large-uncased-stsb: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/yoshitomo-matsubara/bert-large-uncased-stsb/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yoshitomo-matsubara/bert-large-uncased-stsb/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yoshitomo-matsubara/bert-large-uncased-stsb/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 531fbe26d6de4f5bdd9416cfae71c84f00d65626b36fa6efe3942d68ab977006
- Size of remote file:
- 1.34 GB
- SHA256:
- dbd044aa0062f8c65fa5bf0bc36e412c368dfd7ebc3ceb8665f887c59e1041ff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.