Instructions to use Tural/How_to_fine-tune_a_model_for_common_downstream_tasks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tural/How_to_fine-tune_a_model_for_common_downstream_tasks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Tural/How_to_fine-tune_a_model_for_common_downstream_tasks")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Tural/How_to_fine-tune_a_model_for_common_downstream_tasks") model = AutoModelForQuestionAnswering.from_pretrained("Tural/How_to_fine-tune_a_model_for_common_downstream_tasks", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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