Instructions to use Mathoctopus/Parallel_33B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathoctopus/Parallel_33B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Mathoctopus/Parallel_33B")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Mathoctopus/Parallel_33B") model = AutoModel.from_pretrained("Mathoctopus/Parallel_33B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64959bc5985857dae5036fa2bb3b7cc45c803a3832f50734381d33c77c59025e
- Size of remote file:
- 9.75 GB
- SHA256:
- 1c6e2a2f05091ad712cc5f9ccd1aa9491595306a77640007c8ff7b0320c0cc44
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