Instructions to use Adorg/mc231104 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Adorg/mc231104 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Adorg/mc231104", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Adorg/mc231104", trust_remote_code=True) model = AutoModel.from_pretrained("Adorg/mc231104", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 884b6f75dce8173fd7a96cba89865d417df78a098f0ebb165ccd28eabcc8be94
- Size of remote file:
- 454 MB
- SHA256:
- 93cf9936f8b9f7f4341daa418e2ddf31d6c1301f3053dcc036aa1f9d62b7281e
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