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EXL3 · 4.0 bpw · 4.9 GB · Mixture‑of‑Experts · 24 layers × 32 experts[!NOTE] An ExLlamaV3 build ofLiquidAI/LFM2.5-8B-A1Bat 4.0 bits per weight. See Quants for sibling repos at other bit‑widths or browse the collection.
| BPW | Head bits | Calibration rows | Size | Status |
|---|---|---|---|---|
| 4.0 | 8 | 250 | 4.9 GB | this repo |
| 8.0 | 8 | 250 | 9.0 GB | link |
| Loader | Use it for |
|---|---|
| TabbyAPI | OpenAI‑compatible HTTP server. Drop‑in for OpenAI clients. |
| text‑generation‑webui | Local chat UI. Pick the ExLlamaV3 loader from the model dropdown. |
| ExLlamaV3 | Direct Python API for embedding the model in your own code or pipeline. |
1pip install -U huggingface_hub
2
3hf download \
4 blockblockblock/LFM2.5-8B-A1B-exl3-4.0bpw \
5 --local-dir ./LFM2.5-8B-A1B-exl3-4.0bpwquantization_config.json)| Setting | Value |
|---|---|
| Format | EXL3 |
| Bits per weight | 4.0 |
| Head bits | 8 |
| Calibration rows | 250 |
| Codebook | MCG |
| Out‑scales | always |
| Parallel mode | enabled (MoE expert batching) |
[!IMPORTANT] Use and license follow the base model. Quantization adds no additional restrictions. Refer to the upstream repository for terms, citation, and safety documentation.
{org}/{model}-exl3-{bpw}bpw