Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
dense
Generated from Trainer
loss:CachedMultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use reasonwang/embedding-qwen3-1.7b-embedding_ctxt_unicode_shuf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use reasonwang/embedding-qwen3-1.7b-embedding_ctxt_unicode_shuf with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("reasonwang/embedding-qwen3-1.7b-embedding_ctxt_unicode_shuf") 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] - Notebooks
- Google Colab
- Kaggle
Download config.json from reasonwang/embedding-qwen3-1.7b-embedding_ctxt_unicode_shuf: direct link, hf CLI and curl.
- Browser
- Download file 1.35 kB
-
https://huggingface.co/reasonwang/embedding-qwen3-1.7b-embedding_ctxt_unicode_shuf/resolve/main/config.json
- Command line
-
hf download hf://reasonwang/embedding-qwen3-1.7b-embedding_ctxt_unicode_shuf/config.json
-
curl -L -o config.json https://huggingface.co/reasonwang/embedding-qwen3-1.7b-embedding_ctxt_unicode_shuf/resolve/main/config.json
1.35 kB
| { | |
| "architectures": [ | |
| "Qwen3Model" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 151643, | |
| "dtype": "float32", | |
| "eos_token_id": 151643, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6144, | |
| "layer_types": [ | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention", | |
| "full_attention" | |
| ], | |
| "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, | |
| "transformers_version": "4.57.3", | |
| "use_cache": true, | |
| "use_sliding_window": false, | |
| "vocab_size": 151936 | |
| } | |