Instructions to use whitefoxredhell/language_identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whitefoxredhell/language_identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whitefoxredhell/language_identification")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("whitefoxredhell/language_identification") model = AutoModelForSeq2SeqLM.from_pretrained("whitefoxredhell/language_identification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "additional_special_tokens": null, | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "</s>", | |
| "extra_ids": 0, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "sp_model_kwargs": {}, | |
| "tokenizer_class": "T5Tokenizer", | |
| "unk_token": "<unk>" | |
| } | |