Instructions to use nxtcoder19/dummy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nxtcoder19/dummy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nxtcoder19/dummy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nxtcoder19/dummy") model = AutoModelForSequenceClassification.from_pretrained("nxtcoder19/dummy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nxtcoder19/dummy: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/nxtcoder19/dummy/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nxtcoder19/dummy/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nxtcoder19/dummy/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 0b88a993ab6569d760c9cef8f999e0806c632e22ab7319fd243e9166d1c41366
- Size of remote file:
- 438 MB
- SHA256:
- b2598d7866b660c7baa1eb7773f0ea2296cf18ee11fe9e7a87dfaf1a6f21aa36
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