Instructions to use nlp-pw/test-model-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlp-pw/test-model-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nlp-pw/test-model-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nlp-pw/test-model-2") model = AutoModelForSequenceClassification.from_pretrained("nlp-pw/test-model-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nlp-pw/test-model-2: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/nlp-pw/test-model-2/resolve/main/training_args.bin
- Command line
-
hf download hf://nlp-pw/test-model-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nlp-pw/test-model-2/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- 2b3ba8e2abd39a26849c2a8aab727c07c853489908d3790dafd95345134b9330
- Size of remote file:
- 4.6 kB
- SHA256:
- 34d5b32aa6daa982958f3d21a829bd3ff9e120234818ebe4536d63d72e9ddc3b
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