Instructions to use kornwtp/ConGen-BERT-Mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kornwtp/ConGen-BERT-Mini with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kornwtp/ConGen-BERT-Mini") 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 kornwtp/ConGen-BERT-Mini with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kornwtp/ConGen-BERT-Mini") model = AutoModel.from_pretrained("kornwtp/ConGen-BERT-Mini", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from kornwtp/ConGen-BERT-Mini: direct link, hf CLI and curl.
- Browser
- Download file 44.7 MB
-
https://huggingface.co/kornwtp/ConGen-BERT-Mini/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://kornwtp/ConGen-BERT-Mini/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kornwtp/ConGen-BERT-Mini/resolve/main/pytorch_model.bin
44.7 MB
- Xet hash:
- 223df7dd55396be49552380dfb348ac6d30b0a0f2503e5e1ddefa4dcd3a0d838
- Size of remote file:
- 44.7 MB
- SHA256:
- 31649f519b29a42887c6021e69420b1ba6490a1a72bc7610a102df378dcefa2b
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