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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fc406739d4fd8ffc165abdd64c2611cd9eeb02cf447cddc43e205a1153029121
- Size of remote file:
- 9.69 GB
- SHA256:
- ad28e073621fed878932ab382abc52b59bfd746023a225b901474afce7a05ac7
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