Instructions to use aravind-812/roberta-train-json with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aravind-812/roberta-train-json 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="aravind-812/roberta-train-json")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("aravind-812/roberta-train-json") model = AutoModelForQuestionAnswering.from_pretrained("aravind-812/roberta-train-json", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download language_model.bin from aravind-812/roberta-train-json: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/aravind-812/roberta-train-json/resolve/main/language_model.bin
- Command line
-
hf download hf://aravind-812/roberta-train-json/language_model.bin
-
curl -L -o language_model.bin https://huggingface.co/aravind-812/roberta-train-json/resolve/main/language_model.bin
1.42 GB
- Xet hash:
- 7cbb9b34ba7772e06fbcd8c6b4997ae8c1b5696004a20405af57ec96bad13ee2
- Size of remote file:
- 1.42 GB
- SHA256:
- f02da5f1e511f83c3ed01f1fc0820ae3fac82bb7d21245c2b8626890013151f3
路
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