Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use YangsHao/RecBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YangsHao/RecBERT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YangsHao/RecBERT") sentences = [ "汪汪队立大功第1季动画动画冒险剧情本领高强的狗狗巡逻队精通科技的10岁男孩", "超人总动员2喜剧动作动画冒险家庭亲情超级英雄励志超能先生变奶爸超人家族时隔14年强势回归", "星汉灿烂·月升沧海剧情爱情星汉灿烂·月升沧海该剧讲述了程家女名少商", "外星人事件2喜剧科幻剧情山炮大战爆笑来袭传闻,几十年前外星人曾开着飞船造访过下井沟" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use YangsHao/RecBERT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("YangsHao/RecBERT") model = AutoModel.from_pretrained("YangsHao/RecBERT") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
Browse filesThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
- model.safetensors +3 -0
model.safetensors
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