Audio-Text-to-Text
Transformers
Safetensors
Chinese
qwen2_audio
text2text-generation
telecom-fraud
audio-text
qwen2-audio
chinese
speech-understanding
supervised-fine-tuning
Instructions to use JimmyMa99/AntiFraud-SFT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JimmyMa99/AntiFraud-SFT with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("JimmyMa99/AntiFraud-SFT") model = AutoModelForMultimodalLM.from_pretrained("JimmyMa99/AntiFraud-SFT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5c4f0563a1087638031b3844482822153efb0304677c47a28deeb5df48de9ca
- Size of remote file:
- 4.95 GB
- SHA256:
- 0f3a2dcf6d6b49efd26ea1c8890c6b02193eeae4305355c779323943a11bd1dd
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