Instructions to use hf-internal-testing/tiny-random-flaubert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-flaubert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-flaubert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-flaubert") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-flaubert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hf-internal-testing/tiny-random-flaubert: direct link, hf CLI and curl.
- Browser
- Download file 573 Bytes
-
https://huggingface.co/hf-internal-testing/tiny-random-flaubert/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://hf-internal-testing/tiny-random-flaubert/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/hf-internal-testing/tiny-random-flaubert/resolve/main/tokenizer_config.json
573 Bytes
| {"unk_token": "<unk>", "bos_token": "<s>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "</s>", "mask_token": "<special1>", "additional_special_tokens": ["<special0>", "<special1>", "<special2>", "<special3>", "<special4>", "<special5>", "<special6>", "<special7>", "<special8>", "<special9>"], "lang2id": null, "id2lang": null, "do_lowercase_and_remove_accent": true, "do_lower_case": false, "model_max_length": 512, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "flaubert/flaubert_base_cased", "tokenizer_class": "FlaubertTokenizer"} |