Instructions to use nilc-nlp/psst-model-4e-1s-difflib with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nilc-nlp/psst-model-4e-1s-difflib with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="nilc-nlp/psst-model-4e-1s-difflib")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("nilc-nlp/psst-model-4e-1s-difflib") model = AutoModelForSpeechSeq2Seq.from_pretrained("nilc-nlp/psst-model-4e-1s-difflib", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nilc-nlp/psst-model-4e-1s-difflib: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/nilc-nlp/psst-model-4e-1s-difflib/resolve/main/training_args.bin
- Command line
-
hf download hf://nilc-nlp/psst-model-4e-1s-difflib/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nilc-nlp/psst-model-4e-1s-difflib/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 2adc0ba0e692bf02bbcf97856b96bbe1e55251664a537e0b366a2190c15dbf85
- Size of remote file:
- 5.11 kB
- SHA256:
- 33c2ed8ce61828811e5e0e24e6ffd36fbed3d0e6f6a6e2ae198cd2a5ce54d2f0
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