Instructions to use mdp0999/bert_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mdp0999/bert_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mdp0999/bert_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mdp0999/bert_classification") model = AutoModelForSequenceClassification.from_pretrained("mdp0999/bert_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mdp0999/bert_classification: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/mdp0999/bert_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://mdp0999/bert_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mdp0999/bert_classification/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- fa0f3b320f6ab77a9dd4ce88ff95c5bc2b40788b47917f7a3d3237367ab23072
- Size of remote file:
- 3.58 kB
- SHA256:
- 48e691f77a6d2e5b2639d50e80e5021292a0f1c4cd4aa5a4aa1e712e0412d89d
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