Instructions to use nlp-pw/test-model-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlp-pw/test-model-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nlp-pw/test-model-3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nlp-pw/test-model-3") model = AutoModelForSequenceClassification.from_pretrained("nlp-pw/test-model-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nlp-pw/test-model-3: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/nlp-pw/test-model-3/resolve/main/training_args.bin
- Command line
-
hf download hf://nlp-pw/test-model-3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nlp-pw/test-model-3/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- ea19dbaaee07efc27ba8fc687d5c0283eb31a04bda516140e3901c9d07ec5aeb
- Size of remote file:
- 4.6 kB
- SHA256:
- 1a2a3fb95aeb957f108f1742e58672418cc836f6649a9d95500335cb34b94bc6
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