Webcoda AI — 27B (merged full model)
Full merged weights of Webcoda AI, a knowledge assistant fine-tuned from
unsloth/Qwen3.6-27B (dense, bf16) on Webcoda company Q&A. Passed 6/6 factual
validation (identity, founding, leadership, partnerships, Tresillian=Umbraco,
early projects) plus a no-overcorrection regression check.
Recommended: use the GGUF
For local inference on Mac / AMD / NVIDIA, use the quantized GGUF instead — it is
smaller and smoke-tested: hardin/Webcoda-AI-27B-GGUF (Q6_K, ~22 GB).
The LoRA adapter alone is at hardin/Webcoda-AI-27B-LoRA.
Notes on these weights
- Fine-tune: LoRA (r=128) on the language-model attention+MLP projections,
merged to 16-bit. Vision-tower weights are unchanged base weights.
- MTP head removed: the base model's multi-token-prediction (nextn)
speculative-decoding head was stripped. This has no effect on generated
outputs — standard autoregressive inference is identical; only MTP-based
speculative decoding is unavailable.
- Tokenizer:
tokenizer_class set to PreTrainedTokenizerFast for
portability (the base shipped a newer TokenizersBackend class).
- Architecture
Qwen3_5ForConditionalGeneration requires a transformers build
with qwen3_5 support.
