Instructions to use ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR") model = AutoModelForSequenceClassification.from_pretrained("ghatgetanuj/funnel-transformer-xlarge_cls_SentEval-CR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<s>", | |
| "clean_text": true, | |
| "cls_token": "<cls>", | |
| "do_lower_case": true, | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "name_or_path": "funnel-transformer/xlarge", | |
| "pad_token": "<pad>", | |
| "sep_token": "<sep>", | |
| "special_tokens_map_file": "/root/.cache/huggingface/hub/models--funnel-transformer--xlarge/snapshots/a57ed38432204c958ec9df4b8fc999176d10005e/special_tokens_map.json", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "FunnelTokenizer", | |
| "unk_token": "<unk>", | |
| "wordpieces_prefix": "##" | |
| } | |