Instructions to use SanayCo/model_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SanayCo/model_output with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="SanayCo/model_output")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SanayCo/model_output") model = AutoModelForQuestionAnswering.from_pretrained("SanayCo/model_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from SanayCo/model_output: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/SanayCo/model_output/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://SanayCo/model_output/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/SanayCo/model_output/resolve/main/tokenizer_config.json
48 Bytes
| {"do_lower_case": true, "model_max_length": 512} |