Instructions to use tingchih/group_perceiver with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tingchih/group_perceiver with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="tingchih/group_perceiver")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("tingchih/group_perceiver") model = AutoModel.from_pretrained("tingchih/group_perceiver", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": { | |
| "__type": "AddedToken", | |
| "content": "[BOS]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": { | |
| "__type": "AddedToken", | |
| "content": "[CLS]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "eos_token": { | |
| "__type": "AddedToken", | |
| "content": "[EOS]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "mask_token": { | |
| "__type": "AddedToken", | |
| "content": "[MASK]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "model_max_length": 2048, | |
| "pad_token": { | |
| "__type": "AddedToken", | |
| "content": "[PAD]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "sep_token": { | |
| "__type": "AddedToken", | |
| "content": "[SEP]", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "tokenizer_class": "PerceiverTokenizer" | |
| } | |