Instructions to use alinh1803/opt-350-fine-tuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alinh1803/opt-350-fine-tuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="alinh1803/opt-350-fine-tuning")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("alinh1803/opt-350-fine-tuning") model = AutoModelForCausalLM.from_pretrained("alinh1803/opt-350-fine-tuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5ba411513295fe7d3882c56b57a5e14c95003c0ceca83220c8e0a4dfc7596be
- Size of remote file:
- 662 MB
- SHA256:
- 9b3f11ec436ce4dee7ba0460bec022473c31293f475c35891984fe05d573176d
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