Instructions to use sofeamruslan/hf_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sofeamruslan/hf_models with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sofeamruslan/hf_models")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sofeamruslan/hf_models") model = AutoModelForSpeechSeq2Seq.from_pretrained("sofeamruslan/hf_models", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sofeamruslan/hf_models: direct link, hf CLI and curl.
- Browser
- Download file 967 MB
-
https://huggingface.co/sofeamruslan/hf_models/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sofeamruslan/hf_models/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sofeamruslan/hf_models/resolve/main/pytorch_model.bin
967 MB
- Xet hash:
- 0c3290e59313ad1f7d10866b14e60a09d9fdf38c63c70e62772eeaea1f4341ef
- Size of remote file:
- 967 MB
- SHA256:
- cd81bdc9ecf4d33e18de15ef937b2009d57484ed26213f55e5b97a7302cc6219
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