Instructions to use rms7988/final_model_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rms7988/final_model_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rms7988/final_model_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rms7988/final_model_1") model = AutoModelForCTC.from_pretrained("rms7988/final_model_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rms7988/final_model_1: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/rms7988/final_model_1/resolve/main/training_args.bin
- Command line
-
hf download hf://rms7988/final_model_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rms7988/final_model_1/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- d68c7ef0db726f02fb18e263603260ff682a0e0a46a7d3a8ff28a1dfad5be6e3
- Size of remote file:
- 5.11 kB
- SHA256:
- 09b293efdebb9b7ba4c6d9a57dfbe2c838cd235f3cf08b71eb47f29275e2ed45
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