Instructions to use contemmcm/1a7d904346e7c4adfb1de13434e74811 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use contemmcm/1a7d904346e7c4adfb1de13434e74811 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="contemmcm/1a7d904346e7c4adfb1de13434e74811")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("contemmcm/1a7d904346e7c4adfb1de13434e74811") model = AutoModelForSequenceClassification.from_pretrained("contemmcm/1a7d904346e7c4adfb1de13434e74811", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "[CLS]", | |
| "cls_token": "[CLS]", | |
| "eos_token": "[SEP]", | |
| "mask_token": { | |
| "content": "[MASK]", | |
| "lstrip": true, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": "<pad>", | |
| "sep_token": "[SEP]", | |
| "unk_token": "<unk>" | |
| } | |