Feature Extraction
Transformers
Safetensors
qwen3
fp8
compressed-tensors
llm-compressor
vllm
embedding
text-embeddings-inference
Instructions to use DCC-BS/Qwen3-Embedding-4B-FP8-Dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DCC-BS/Qwen3-Embedding-4B-FP8-Dynamic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DCC-BS/Qwen3-Embedding-4B-FP8-Dynamic")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DCC-BS/Qwen3-Embedding-4B-FP8-Dynamic") model = AutoModel.from_pretrained("DCC-BS/Qwen3-Embedding-4B-FP8-Dynamic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 379 Bytes
70cb703 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"model_id": "Qwen/Qwen3-Embedding-4B",
"kind": "embedding",
"scheme": "FP8_DYNAMIC",
"ignore": [
"lm_head"
],
"source_bytes": 8043592088,
"output_bytes": 4412516640,
"seconds": 5.561132976989029,
"copied_assets": [
"modules.json",
"config_sentence_transformers.json",
"1_Pooling/config.json"
],
"created_at": "2026-08-05T12:28:36+00:00"
}
|