Instructions to use HIT-TMG/JevEmbed-Qwen3-Embedding-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HIT-TMG/JevEmbed-Qwen3-Embedding-4B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HIT-TMG/JevEmbed-Qwen3-Embedding-4B") 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] - Notebooks
- Google Colab
- Kaggle
Download added_tokens.json from HIT-TMG/JevEmbed-Qwen3-Embedding-4B: direct link, hf CLI and curl.
- Browser
- Download file 605 Bytes
-
https://huggingface.co/HIT-TMG/JevEmbed-Qwen3-Embedding-4B/resolve/main/added_tokens.json
- Command line
-
hf download hf://HIT-TMG/JevEmbed-Qwen3-Embedding-4B/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/HIT-TMG/JevEmbed-Qwen3-Embedding-4B/resolve/main/added_tokens.json
605 Bytes
| { | |
| "</tool_call>": 151658, | |
| "<tool_call>": 151657, | |
| "<|box_end|>": 151649, | |
| "<|box_start|>": 151648, | |
| "<|endoftext|>": 151643, | |
| "<|file_sep|>": 151664, | |
| "<|fim_middle|>": 151660, | |
| "<|fim_pad|>": 151662, | |
| "<|fim_prefix|>": 151659, | |
| "<|fim_suffix|>": 151661, | |
| "<|im_end|>": 151645, | |
| "<|im_start|>": 151644, | |
| "<|image_pad|>": 151655, | |
| "<|object_ref_end|>": 151647, | |
| "<|object_ref_start|>": 151646, | |
| "<|quad_end|>": 151651, | |
| "<|quad_start|>": 151650, | |
| "<|repo_name|>": 151663, | |
| "<|video_pad|>": 151656, | |
| "<|vision_end|>": 151653, | |
| "<|vision_pad|>": 151654, | |
| "<|vision_start|>": 151652 | |
| } | |