Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Ahmed107/EOS_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmed107/EOS_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ahmed107/EOS_bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmed107/EOS_bert") model = AutoModelForSequenceClassification.from_pretrained("Ahmed107/EOS_bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ahmed107/EOS_bert: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/Ahmed107/EOS_bert/resolve/main/training_args.bin
- Command line
-
hf download hf://Ahmed107/EOS_bert/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ahmed107/EOS_bert/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 86ea5b49af5408626012522d149de33cfb4d7b91c17cc61c4e011b7d6da6b1e1
- Size of remote file:
- 5.24 kB
- SHA256:
- 0214e9dfb1b574f188b51789b92e28e35428c3299613258ee57045a28d47c4d3
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