Instructions to use PantagrueLLM/jargon-general-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PantagrueLLM/jargon-general-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="PantagrueLLM/jargon-general-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("PantagrueLLM/jargon-general-base", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 943b20be31c4d60598b84c8c14e51f34da0369fd6c530752a4cd47554fbf5619
- Size of remote file:
- 582 MB
- SHA256:
- d114841c7eeda6e5564bbee9b9888ed91a536d6b3594f04df31bd6f9dc013311
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