Instructions to use abhinavp/dummy_run with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abhinavp/dummy_run with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("abhinavp/dummy_run", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from abhinavp/dummy_run: direct link, hf CLI and curl.
- Browser
- Download file 323 Bytes
-
https://huggingface.co/abhinavp/dummy_run/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://abhinavp/dummy_run/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/abhinavp/dummy_run/resolve/main/tokenizer_config.json
323 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<eos>", | |
| "max_length": null, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<pad>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "tokenizer_class": "PreTrainedTokenizerFast", | |
| "unk_token": "<unk>" | |
| } | |