Instructions to use VaidehiBhat007/fine_tuned_emo_classif with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VaidehiBhat007/fine_tuned_emo_classif with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="VaidehiBhat007/fine_tuned_emo_classif")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("VaidehiBhat007/fine_tuned_emo_classif") model = AutoModelForAudioClassification.from_pretrained("VaidehiBhat007/fine_tuned_emo_classif", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from VaidehiBhat007/fine_tuned_emo_classif: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/VaidehiBhat007/fine_tuned_emo_classif/resolve/main/training_args.bin
- Command line
-
hf download hf://VaidehiBhat007/fine_tuned_emo_classif/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/VaidehiBhat007/fine_tuned_emo_classif/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 17d0a99b5f96b8469457e5eeead49eefce2cfad5331ecc42c20034bdada23904
- Size of remote file:
- 5.11 kB
- SHA256:
- 1e137bac3cb2ab06df475cd83b6eb47d5e5ae86d643261faaefc3073c3052f85
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