Instructions to use SinghManish/TransformersModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SinghManish/TransformersModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SinghManish/TransformersModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("SinghManish/TransformersModel") model = AutoModel.from_pretrained("SinghManish/TransformersModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from SinghManish/TransformersModel: direct link, hf CLI and curl.
- Browser
- Download file 1.13 GB
-
https://huggingface.co/SinghManish/TransformersModel/resolve/main/tf_model.h5
- Command line
-
hf download hf://SinghManish/TransformersModel/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/SinghManish/TransformersModel/resolve/main/tf_model.h5
1.13 GB
- Xet hash:
- ffb442aa09614ae91c5e77cb3fe8ef8f07b30512b8eefaa275f627edf06c07ed
- Size of remote file:
- 1.13 GB
- SHA256:
- 2bdfffdfe3875b8f55c1a47958f0ba91bcb398c15ae4e88c84b6cbed73d19bd5
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