Feature Extraction
Transformers
Safetensors
sentence-transformers
English
Chinese
qwen3
embedding
sentence-similarity
awq
int4
w4a16
compressed-tensors
vllm
mteb
blackwell
text-embeddings-inference
Instructions to use LostGentoo/Qwen3-Embedding-8B-AWQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LostGentoo/Qwen3-Embedding-8B-AWQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LostGentoo/Qwen3-Embedding-8B-AWQ")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LostGentoo/Qwen3-Embedding-8B-AWQ") model = AutoModel.from_pretrained("LostGentoo/Qwen3-Embedding-8B-AWQ") - sentence-transformers
How to use LostGentoo/Qwen3-Embedding-8B-AWQ with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("LostGentoo/Qwen3-Embedding-8B-AWQ") 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
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