Instructions to use Ulangi/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ulangi/checkpoints with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="Ulangi/checkpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Ulangi/checkpoints") model = AutoModelForQuestionAnswering.from_pretrained("Ulangi/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 403 Bytes
2f3c425 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"added_tokens_decoder": {
"40030": {
"content": "[PAD]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"clean_up_tokenization_spaces": true,
"extra_special_tokens": {},
"model_max_length": 1000000000000000019884624838656,
"pad_token": "[PAD]",
"tokenizer_class": "PreTrainedTokenizerFast"
}
|