Sentence Similarity
Transformers
Safetensors
sentence-transformers
llama
feature-extraction
custom_code
text-embeddings-inference
Instructions to use facebook/drama-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/drama-large with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/drama-large", trust_remote_code=True) model = AutoModel.from_pretrained("facebook/drama-large", trust_remote_code=True, device_map="auto") - sentence-transformers
How to use facebook/drama-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("facebook/drama-large", trust_remote_code=True) sentences = [ "هذا شخص سعيد", "هذا كلب سعيد", "هذا شخص سعيد جدا", "اليوم هو يوم مشمس" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download 1_Pooling/config.json from facebook/drama-large: direct link, hf CLI and curl.
- Browser
- Download file 297 Bytes
-
https://huggingface.co/facebook/drama-large/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://facebook/drama-large/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/facebook/drama-large/resolve/main/1_Pooling/config.json
297 Bytes
| { | |
| "word_embedding_dimension": 1024, | |
| "pooling_mode_cls_token": false, | |
| "pooling_mode_mean_tokens": true, | |
| "pooling_mode_max_tokens": false, | |
| "pooling_mode_mean_sqrt_len_tokens": false, | |
| "pooling_mode_weightedmean_tokens": false, | |
| "pooling_mode_lasttoken": false, | |
| "include_prompt": true | |
| } |