Instructions to use UCSC-VLAA/m1-32B-1K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UCSC-VLAA/m1-32B-1K with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="UCSC-VLAA/m1-32B-1K")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("UCSC-VLAA/m1-32B-1K") model = AutoModelForCausalLM.from_pretrained("UCSC-VLAA/m1-32B-1K") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
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- 4.72 GB xet
- 4.47 GB xet
- 4.47 GB xet
- 4.72 GB xet
- 4.47 GB xet
- 4.47 GB xet
- 4.72 GB xet
- 4.47 GB xet
- 4.47 GB xet
- 4.72 GB xet
- 4.47 GB xet
- 4.47 GB xet
- 4.72 GB xet
- 4.47 GB xet
- 4.47 GB xet
- 4.72 GB xet
- 4.47 GB xet
- 4.47 GB xet
- 4.72 GB xet
- 4.47 GB xet
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- 63.2 kB
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