Instructions to use rezaFarsh/binary_support_eval_base_198_voices_transcriptions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rezaFarsh/binary_support_eval_base_198_voices_transcriptions with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="rezaFarsh/binary_support_eval_base_198_voices_transcriptions")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("rezaFarsh/binary_support_eval_base_198_voices_transcriptions") model = AutoModelForSequenceClassification.from_pretrained("rezaFarsh/binary_support_eval_base_198_voices_transcriptions") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fae13303e9b486079dcc020ba7ab7667a02488ce05acb4770f7516d87f3b0840
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size 669455360
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