Instructions to use linktimecloud/my_awesome_model_classification_w_adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linktimecloud/my_awesome_model_classification_w_adapter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="linktimecloud/my_awesome_model_classification_w_adapter")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("linktimecloud/my_awesome_model_classification_w_adapter") model = AutoModelForSequenceClassification.from_pretrained("linktimecloud/my_awesome_model_classification_w_adapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 380 Bytes
866e856 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
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"errors": "replace",
"mask_token": "<mask>",
"model_max_length": 512,
"name_or_path": "roberta-base",
"pad_token": "<pad>",
"sep_token": "</s>",
"special_tokens_map_file": null,
"tokenizer_class": "RobertaTokenizer",
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