Instructions to use mor40/BulBERT-cinexio-5pochs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mor40/BulBERT-cinexio-5pochs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mor40/BulBERT-cinexio-5pochs")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mor40/BulBERT-cinexio-5pochs") model = AutoModelForSequenceClassification.from_pretrained("mor40/BulBERT-cinexio-5pochs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from mor40/BulBERT-cinexio-5pochs: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/mor40/BulBERT-cinexio-5pochs/resolve/main/training_args.bin
- Command line
-
hf download hf://mor40/BulBERT-cinexio-5pochs/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mor40/BulBERT-cinexio-5pochs/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 697b82f89983cbe4187910f799542314662e116f8af093337f8177e54a34973e
- Size of remote file:
- 4.54 kB
- SHA256:
- d10f1dcb6a2c8a50bb39ae205e1d7aa5d0e2a9a66c9f4bbd98fa1a186a18c360
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