Feature Extraction
Transformers
Safetensors
English
Chinese
qwen3
text-generation
zen
zen-embedding
zenlm
hanzo
embedding
text-embeddings-inference
Instructions to use zenlm/zen-embedding-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenlm/zen-embedding-4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="zenlm/zen-embedding-4B")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("zenlm/zen-embedding-4B") model = AutoModelForMultimodalLM.from_pretrained("zenlm/zen-embedding-4B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8407b8a5fc62ae108ee9c4cc91f05d5f2bcacedcf3b2e374505ec6a4d9b92c0f
- Size of remote file:
- 11.4 MB
- SHA256:
- 83cdf8c3a34f68862319cb1810ee7b1e2c0a44e0864ae930194ddb76bb7feb8d
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