Instructions to use sunitha/config_distilbert_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sunitha/config_distilbert_model 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="sunitha/config_distilbert_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sunitha/config_distilbert_model") model = AutoModelForQuestionAnswering.from_pretrained("sunitha/config_distilbert_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sunitha/config_distilbert_model: direct link, hf CLI and curl.
- Browser
- Download file 267 MB
-
https://huggingface.co/sunitha/config_distilbert_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sunitha/config_distilbert_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sunitha/config_distilbert_model/resolve/main/pytorch_model.bin
267 MB
- Xet hash:
- 9c88f1f42507a6ce6110ce589a23568c1223fb27fd7c6f603028d80ecacebe2a
- Size of remote file:
- 267 MB
- SHA256:
- 9b7a6d7f80bdb28949bf36fc7bb1db0c4efadfaf11f69db9d7d5d873df5165ed
路
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