Instructions to use r2d2/stsb-bertweet-base-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use r2d2/stsb-bertweet-base-v0 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("r2d2/stsb-bertweet-base-v0") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use r2d2/stsb-bertweet-base-v0 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("r2d2/stsb-bertweet-base-v0") model = AutoModel.from_pretrained("r2d2/stsb-bertweet-base-v0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"normalization": false, "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "model_max_length": 128, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "output/training_stsbenchmark_vinai-bertweet-base-2022-02-18_13-53-02/", "tokenizer_class": "BertweetTokenizer"} |