canine-c
Pretrained CANINE model on 104 languages using a masked language modeling (MLM) objective. It was introduced in the paper CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation and first released in this repository.
Params
130 M
Context
16,384
Downloads 30d
439 K
Likes
37
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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 | 0.5 GB | 1.1 GB | ✅ Runs comfortably |
| model.safetensors (bf16, full) | bf16 + 16K ctx | 0.5 GB | 1.1 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
- CanineModel
- Parameters
- 130 M
- Tensor type
- F32
- Context length
- 16,384
- Layers / heads
- 12 / 12
- Licence
- apache-2.0
- First seen on the Hub
- 2022-03-02
- Training datasets
- bookcorpus, wikipedia
- Added to our catalog
- 2026-08-14
Compare with any feature-extraction model