Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use elopezlopez/roberta-base_fold_1_binary_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elopezlopez/roberta-base_fold_1_binary_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="elopezlopez/roberta-base_fold_1_binary_v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elopezlopez/roberta-base_fold_1_binary_v1") model = AutoModelForSequenceClassification.from_pretrained("elopezlopez/roberta-base_fold_1_binary_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from elopezlopez/roberta-base_fold_1_binary_v1: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/elopezlopez/roberta-base_fold_1_binary_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://elopezlopez/roberta-base_fold_1_binary_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/elopezlopez/roberta-base_fold_1_binary_v1/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- c8066880f2e611b9d2ef79036c2d80c71b3d0a752e78022287e9cf9b55678895
- Size of remote file:
- 499 MB
- SHA256:
- 9f77942d340157195784c5821b705766a73d9747a4099c3d2a9243b6cf908337
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