greglechin/Swift-1.5-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16

image-text-to-text model by greglechin

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GPTQ-Int4 quantization of ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-MTP, built for Intel Arc / vLLM XPU with the MTP head preserved in BF16 so native speculative decoding still works. The recipe is a reproduction of kernelogic/Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16, applied to the Swift lineage instead of the JonathanColetti one. Same quantizer version, same config, same MTP handling. Quantizing this model naively breaks speculative decoding. The 15 mtp. tensors are the draft head; if they get quantized along with everything else, draft acceptance collapses and you lose roughly half your decode speed. The fix is one line of quantize config: The result has 400 quantized weight tensors (I32) + 15 preserved BF16 MTP tensors. There is a second, less obvious requirement. transformers' Qwen35 declares keystoignoreonloadunexpected = [r"^mtp."], so the draft tensors are dropped at load and never become modules — the dynamic exclusion on its own emits a checkpoint with no draft head at all, silently. What writes them…

greglechin/Swift-1.5-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16 on Hugging Face A short preview, not the full document.

Read the full model card ↗ · Preview checked 2026-09-25T07:36:41.341Z

Inside the original model card — Document outline
  1. Swift-1.5-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16
  2. Why this exists
  3. Provenance
  4. Quantization
  5. Measured performance
  6. Serving (vLLM XPU)
  7. Three things that will bite you
  8. Limitations — please read
  9. Licence
  10. Credits

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Model overview

greglechin/Swift-1.5-Qwen3.8-27B-Uncensored-GPTQ-Int4-sym-G128-MTP-BF16 is a image-text-to-text model repository published by greglechin on Hugging Face. The source reports the transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
image-text-to-text
Library
transformers
Recent downloads (30 days)
0
Cumulative likes
1
Hugging Face trending score
1
Reported safetensors parameters
27,781,427,952
Architecture
Qwen3_5ForConditionalGeneration
License
other
Access
Not gated by Hugging Face
Created
2026-09-25T05:54:55.000Z
Last modified
2026-09-25T05:59:27.000Z

Compatibility and lineage

Reported languages: en, zh

Reported base models: ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-MTP

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-09-25T06:37:40.528Z. Daily imports are snapshots, not real-time monitoring.

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