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, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("zenlm/zen-embedding-4B") model = AutoModelForCausalLM.from_pretrained("zenlm/zen-embedding-4B") - Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| library_name: transformers | |
| pipeline_tag: feature-extraction | |
| language: | |
| - en | |
| - zh | |
| tags: | |
| - zen | |
| - zen-embedding | |
| - zenlm | |
| - hanzo | |
| - embedding | |
| # Zen Embedding 4B | |
| 4B-parameter sentence-embedding model for retrieval-augmented generation, semantic search, and dense retrieval. Part of the Zen embedding family. | |
| ## Hosted via Hanzo gateway | |
| Served at `api.hanzo.ai` as `zen-embedding-4b`. | |
| ## Files | |
| Native HuggingFace `safetensors` weights, loadable directly with `transformers`: | |
| ```python | |
| from transformers import AutoModel, AutoTokenizer | |
| m = AutoModel.from_pretrained("zenlm/zen-embedding-4B") | |
| t = AutoTokenizer.from_pretrained("zenlm/zen-embedding-4B") | |
| ``` | |
| For GGUF / Ollama deployment, see [zenlm/zen-embedding-4B-GGUF](https://huggingface.co/zenlm/zen-embedding-4B-GGUF). | |