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:
- df49b75b51f18d6b8b23cf64495eebd3a25094f15ca3d4fa45254a9e4a010bfc
- Size of remote file:
- 9.75 GB
- SHA256:
- e51b9a8917179aa3daf14b50cad31a4c4b047d5d6d5adbcad55490aed8b766b3
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