Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use elopezlopez/distilbert-base-uncased_fold_3_binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use elopezlopez/distilbert-base-uncased_fold_3_binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="elopezlopez/distilbert-base-uncased_fold_3_binary")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("elopezlopez/distilbert-base-uncased_fold_3_binary") model = AutoModelForSequenceClassification.from_pretrained("elopezlopez/distilbert-base-uncased_fold_3_binary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from elopezlopez/distilbert-base-uncased_fold_3_binary: direct link, hf CLI and curl.
- Browser
- Download file 3.38 kB
-
https://huggingface.co/elopezlopez/distilbert-base-uncased_fold_3_binary/resolve/main/training_args.bin
- Command line
-
hf download hf://elopezlopez/distilbert-base-uncased_fold_3_binary/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/elopezlopez/distilbert-base-uncased_fold_3_binary/resolve/main/training_args.bin
3.38 kB
- Xet hash:
- d0c43a56f6d0a21cf47120a3def9a18c2c2c8031a852e428c92940c8e5f5dddb
- Size of remote file:
- 3.38 kB
- SHA256:
- d6e47451790f54c48a6038bbcfcf5ebb9d76f8c194afb94a57fe349ef6a89eb0
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