Instructions to use lukecarlate/FinBERT_P_SM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukecarlate/FinBERT_P_SM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="lukecarlate/FinBERT_P_SM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("lukecarlate/FinBERT_P_SM") model = AutoModelForMaskedLM.from_pretrained("lukecarlate/FinBERT_P_SM") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "do_basic_tokenize": true, | |
| "do_lower_case": true, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "name_or_path": "ProsusAI/finbert", | |
| "never_split": null, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "special_tokens_map_file": "C:\\Users\\ANDLab3/.cache\\huggingface\\hub\\models--ProsusAI--finbert\\snapshots\\4556d13015211d73dccd3fdd39d39232506f3e43\\special_tokens_map.json", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |