Feature Extraction
Transformers
Safetensors
English
Chinese
qwen3
embedding
retriever
RAG
Agentic
Skills
text-embeddings-inference
Instructions to use ttchungc/InsightEmb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ttchungc/InsightEmb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ttchungc/InsightEmb")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ttchungc/InsightEmb") model = AutoModel.from_pretrained("ttchungc/InsightEmb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a4af02de3ebe1f083cd88863235e9d0c0f5865776b861bbe0bbf939fa4930b6
- Size of remote file:
- 7.93 kB
- SHA256:
- a9f0933396899b1a4a5b9874eccd365f731a5c4f775c3d81bbe3d34b22adf611
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