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:
- 8918050e33ac0fd5c9043873ff829c4695a646789f9d5f75695784a46446b6ca
- Size of remote file:
- 11.4 MB
- SHA256:
- b1488be6077b34b8add52f471a1f6d8628b5f26ae4b3c1782bd43de31367e8f1
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