Instructions to use mkddatascience/mechanical-llm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkddatascience/mechanical-llm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mkddatascience/mechanical-llm")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mkddatascience/mechanical-llm") model = AutoModel.from_pretrained("mkddatascience/mechanical-llm") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 1764d8b
Pushing the fine-tuned model
Browse files- tokenizer.json +0 -0
- tokenizer.model +3 -0
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oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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size 493443
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