Instructions to use hf-tiny-model-private/tiny-random-LEDForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-LEDForQuestionAnswering 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="hf-tiny-model-private/tiny-random-LEDForQuestionAnswering")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LEDForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-LEDForQuestionAnswering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-LEDForQuestionAnswering: direct link, hf CLI and curl.
- Browser
- Download file 1.23 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-LEDForQuestionAnswering/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-LEDForQuestionAnswering@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-LEDForQuestionAnswering/resolve/refs%2Fpr%2F1/model.safetensors
1.23 MB
- Xet hash:
- b525c56497f2f902ca6c48b0867d8da19725d3cf738c83549d9e44ade9a27e8d
- Size of remote file:
- 1.23 MB
- SHA256:
- 7ff713d5d498b2b81c1936245bb76cfcae54a802f7ebbc4076bdcd9d2ca596bd
路
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