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:
- e5f7e5ac3d6922154e20a7ecf09380b0bb54d098d9f28202dc13ded1e6cdd759
- Size of remote file:
- 4.99 GB
- SHA256:
- ea62fbcf9fde03eac95e40c4ca573fb5be207e0a55258424e0e8515b719cf7a0
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