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 training_args.bin from elopezlopez/roberta-base_fold_1_binary_v1: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/elopezlopez/roberta-base_fold_1_binary_v1/resolve/main/training_args.bin
- Command line
-
hf download hf://elopezlopez/roberta-base_fold_1_binary_v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/elopezlopez/roberta-base_fold_1_binary_v1/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- 7763939c4f8f467d53ca70611b405bff96c1ae02dfadb8b5d20e15c399078413
- Size of remote file:
- 3.38 kB
- SHA256:
- 76bc88f7801218af1c7c34eb53cb4fc9c00133f006dfaed8f97c5317de74e14d
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