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:
- ab049a0932c0f7f9e7a32d46974b3ded1ac7b764a5ee37e52898cee742902b6b
- Size of remote file:
- 1.43 GB
- SHA256:
- ac44f70ce7f07cd871aeb0fe9a2bc9692cd237a7513f88a8b0552427c00fc19f
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