Feature Extraction
sentence-transformers
Safetensors
Transformers
qwen3
text-generation
sentence-similarity
text-embeddings-inference
quantized
8-bit precision
Instructions to use techAInewb/Qwen3-Embedding-0.6B-INT8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use techAInewb/Qwen3-Embedding-0.6B-INT8 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("techAInewb/Qwen3-Embedding-0.6B-INT8") 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 techAInewb/Qwen3-Embedding-0.6B-INT8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="techAInewb/Qwen3-Embedding-0.6B-INT8")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("techAInewb/Qwen3-Embedding-0.6B-INT8") model = AutoModelForCausalLM.from_pretrained("techAInewb/Qwen3-Embedding-0.6B-INT8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download quantization_map.json from techAInewb/Qwen3-Embedding-0.6B-INT8: direct link, hf CLI and curl.
- Browser
- Download file 17.1 kB
-
https://huggingface.co/techAInewb/Qwen3-Embedding-0.6B-INT8/resolve/main/quantization_map.json
- Command line
-
hf download hf://techAInewb/Qwen3-Embedding-0.6B-INT8/quantization_map.json
-
curl -L -o quantization_map.json https://huggingface.co/techAInewb/Qwen3-Embedding-0.6B-INT8/resolve/main/quantization_map.json
17.1 kB
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