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 tokenizer_config.json from aravind-812/roberta-train-json: direct link, hf CLI and curl.
- Browser
- Download file 420 Bytes
-
https://huggingface.co/aravind-812/roberta-train-json/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://aravind-812/roberta-train-json/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/aravind-812/roberta-train-json/resolve/main/tokenizer_config.json
420 Bytes
| {"do_lower_case": false, "model_max_length": 512, "bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>", "special_tokens_map_file": "/root/.cache/torch/transformers/cc43f10372bf085733243a9db0765736e2dc015d48f6e8a96de4be0f6ef6a9fc.16f949018cf247a2ea7465a74ca9a292212875e5fd72f969e0807011e7f192e4", "full_tokenizer_file": null} |