Instructions to use ROGRANMAR/output_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ROGRANMAR/output_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ROGRANMAR/output_dir")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ROGRANMAR/output_dir") model = AutoModelForSpeechSeq2Seq.from_pretrained("ROGRANMAR/output_dir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ROGRANMAR/output_dir: direct link, hf CLI and curl.
- Browser
- Download file 151 MB
-
https://huggingface.co/ROGRANMAR/output_dir/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ROGRANMAR/output_dir/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ROGRANMAR/output_dir/resolve/main/pytorch_model.bin
151 MB
- Xet hash:
- 8d192d1876c4df4d9ad90d999b646d29b753af1dc3bdcb0a37892c9d242b8846
- Size of remote file:
- 151 MB
- SHA256:
- 8bc6cb26051aee00bf27fa6fc6efa5cf5b13085961477042aff7ca9f2c6c4216
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