Instructions to use jonas-mo/trainer_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonas-mo/trainer_output with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jonas-mo/trainer_output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from jonas-mo/trainer_output: direct link, hf CLI and curl.
- Browser
- Download file 402 Bytes
-
https://huggingface.co/jonas-mo/trainer_output/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://jonas-mo/trainer_output/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/jonas-mo/trainer_output/resolve/main/tokenizer_config.json
402 Bytes
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<|begin_of_text|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|eot_id|>", | |
| "is_local": false, | |
| "local_files_only": false, | |
| "model_input_names": [ | |
| "input_ids", | |
| "attention_mask" | |
| ], | |
| "model_max_length": 131072, | |
| "pad_token": "<|eot_id|>", | |
| "padding_side": "right", | |
| "tokenizer_class": "TokenizersBackend", | |
| "unk_token": null | |
| } | |