Instructions to use Magjot/Second_test_LLM_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Magjot/Second_test_LLM_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="Magjot/Second_test_LLM_3")# Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("Magjot/Second_test_LLM_3") model = AutoModelForTextToSpectrogram.from_pretrained("Magjot/Second_test_LLM_3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload requirements.txt
Browse files- requirements.txt +5 -0
requirements.txt
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transformers>=4.41.0
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torch>=2.2.0
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protobuf>=3.20.0
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peft>=0.10.0 # only if you use LoRA (optional now)
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accelerate>=0.30.0 # if you use device_map="auto"
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