Instructions to use TencentBAC/Conan-embedding-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use TencentBAC/Conan-embedding-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("TencentBAC/Conan-embedding-v1") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
技术报告中的iteration的疑问
#5
by sthsf - opened
请教一下,技术报告中提到fine-tuning阶段的数据量大概是4.2M左右,按照fine-tuning的算力和batch_size的设置,figure 4里面的500个iteration是不是一个完整的epoch都没有走完?
哈喽你好Figure 4是用于说明Cross-GPU Batch Balance策略和朴素策略下的Loss收敛的变化,只选取的训练前期的Loss-Iter曲线并不是完整曲线,用于比较明确的说明收益。
Vurkty changed discussion status to closed