Instructions to use vstudent/dummy-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vstudent/dummy-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vstudent/dummy-model")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vstudent/dummy-model") model = AutoModelForMaskedLM.from_pretrained("vstudent/dummy-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from vstudent/dummy-model: direct link, hf CLI and curl.
- Browser
- Download file 543 MB
-
https://huggingface.co/vstudent/dummy-model/resolve/main/tf_model.h5
- Command line
-
hf download hf://vstudent/dummy-model/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/vstudent/dummy-model/resolve/main/tf_model.h5
543 MB
- Xet hash:
- dc68071eb25624500dd3cb2777718ec214da6aef2d5ef2c8d99aec235cf4cf8d
- Size of remote file:
- 543 MB
- SHA256:
- b7f2fd11de7e3f6c2273b432cbc0d324924b3b1eafe8b0b6d379688e50c58699
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