Instructions to use hf-tiny-model-private/tiny-random-FSMTModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-FSMTModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-FSMTModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-FSMTModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-FSMTModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hf-tiny-model-private/tiny-random-FSMTModel: direct link, hf CLI and curl.
- Browser
- Download file 298 Bytes
-
https://huggingface.co/hf-tiny-model-private/tiny-random-FSMTModel/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-FSMTModel/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/hf-tiny-model-private/tiny-random-FSMTModel/resolve/main/tokenizer_config.json
298 Bytes
| { | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "do_lower_case": false, | |
| "langs": [ | |
| "en", | |
| "ru" | |
| ], | |
| "model_max_length": 20, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "special_tokens_map_file": null, | |
| "tokenizer_class": "FSMTTokenizer", | |
| "unk_token": "<unk>" | |
| } | |