Instructions to use linhphanff/phobert-base-v2-flash-attention with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use linhphanff/phobert-base-v2-flash-attention with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="linhphanff/phobert-base-v2-flash-attention")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("linhphanff/phobert-base-v2-flash-attention") model = AutoModel.from_pretrained("linhphanff/phobert-base-v2-flash-attention") - Notebooks
- Google Colab
- Kaggle
| { | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "PhobertTokenizer", | |
| "unk_token": "<unk>" | |
| } | |