Instructions to use kardosdrur/dfm-encoder-small-v1-angle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kardosdrur/dfm-encoder-small-v1-angle with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kardosdrur/dfm-encoder-small-v1-angle") 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 kardosdrur/dfm-encoder-small-v1-angle with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kardosdrur/dfm-encoder-small-v1-angle") model = AutoModel.from_pretrained("kardosdrur/dfm-encoder-small-v1-angle", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from kardosdrur/dfm-encoder-small-v1-angle: direct link, hf CLI and curl.
- Browser
- Download file 2.3 MB
-
https://huggingface.co/kardosdrur/dfm-encoder-small-v1-angle/resolve/main/tokenizer.json
- Command line
-
hf download hf://kardosdrur/dfm-encoder-small-v1-angle/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/kardosdrur/dfm-encoder-small-v1-angle/resolve/main/tokenizer.json
2.3 MB
File too large to display, you can check the raw version instead.