text2vec-base-chinese
It maps sentences to a 768 dimensional dense vector space and can be used for tasks like sentence embeddings, text matching or semantic search.
Params
100 M
Context
512
Downloads 30d
824 K
Likes
799
Download history
daily snapshots · 10 days824 K784 K
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Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.4 GB | 1.0 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- BertModel
- Parameters
- 100 M
- Tensor type
- F32
- Context length
- 512
- Vocabulary
- 21,128
- Layers / heads
- 12 / 12
- Licence
- apache-2.0
- First seen on the Hub
- 2022-03-02
- Training datasets
- shibing624/nli_zh
- Added to our catalog
- 2026-07-28
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