Sentence Similarity
sentence-transformers
Safetensors
Transformers
Persian
English
qwen3
text-generation
persian
text-embeddings
dense-retrieval
semantic-search
knowledge-distillation
feature-extraction
text-embeddings-inference
Instructions to use Yaldat/Yalda-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Yaldat/Yalda-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Yaldat/Yalda-Embedding") 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] - Transformers
How to use Yaldat/Yalda-Embedding with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Yaldat/Yalda-Embedding") model = AutoModelForCausalLM.from_pretrained("Yaldat/Yalda-Embedding", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Yaldat/Yalda-Embedding: direct link, hf CLI and curl.
- Browser
- Download file 727 Bytes
-
https://huggingface.co/Yaldat/Yalda-Embedding/resolve/main/config.json
- Command line
-
hf download hf://Yaldat/Yalda-Embedding/config.json
-
curl -L -o config.json https://huggingface.co/Yaldat/Yalda-Embedding/resolve/main/config.json
727 Bytes
| { | |
| "architectures": [ | |
| "Qwen3ForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 151643, | |
| "eos_token_id": 151643, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "max_position_embeddings": 32768, | |
| "max_window_layers": 28, | |
| "model_type": "qwen3", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 8, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": null, | |
| "rope_theta": 1000000, | |
| "sliding_window": null, | |
| "tie_word_embeddings": true, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.51.3", | |
| "use_cache": true, | |
| "use_sliding_window": false, | |
| "vocab_size": 151669 | |
| } | |