Instructions to use nxtcoder36/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nxtcoder36/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nxtcoder36/dummy-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nxtcoder36/dummy-model") model = AutoModelForMaskedLM.from_pretrained("nxtcoder36/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from nxtcoder36/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/nxtcoder36/dummy-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://nxtcoder36/dummy-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/nxtcoder36/dummy-model/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 5db57bb7a09a0481a4b3282988488391975160f0ab152a8ee9cb96927e96effc
- Size of remote file:
- 443 MB
- SHA256:
- 61f34945015026c448d0f9329fa178504bef78c17a3a847bd3ac2dcdf4a4ed8e
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