imbutus/YuYu1015-Ornith-1.0-35B-abliterated

Ornith 1.0 35B abliterated — vLLM-ready mirror

Hosted inference: run this model on demand at imbutus.com.

A drop-in, serving-ready mirror of YuYu1015/YuYu1015-Ornith-1.0-35B-abliterated.

The weights are identical to the source repo — the only change is that the missing multimodal preprocessor configuration files were added so the model loads on vLLM (and any transformers-based multimodal loader) without patching.

Why this mirror exists

config.json declares a multimodal model:

"architectures": ["Qwen3_5MoeForConditionalGeneration"],
"model_type": "qwen3_5_moe",
"vision_config": { ... },
"image_token_id": ..., "video_token_id": ...

so vLLM initializes the vision path and requires an image/video processor config. The source abliterated re-upload did not include those files, so loading it directly fails with:

OSError: Can't load image processor for
'YuYu1015/YuYu1015-Ornith-1.0-35B-abliterated' ... make sure ...
contains a preprocessor_config.json file

What was added

Copied verbatim from the official base model deepreinforce-ai/Ornith-1.0-35B:

• preprocessor_config.json
• processor_config.json
• video_preprocessor_config.json
• vocab.json

Everything else (the two safetensors shards, config.json, tokenizer.json, chat_template.jinja, etc.) is a byte-for-byte copy of the source repo.

Serving with vLLM

vllm serve imbutus/Ornith-1.0-35B-abliterated \
  --trust-remote-code \
  --max-model-len 131072 \
  --reasoning-parser qwen3 \
  --enable-auto-tool-choice --tool-call-parser qwen3_coder

Fits a single 96 GB GPU (~70 GB bf16 weights). Native context 262144, capped here to 131072 for single-GPU KV cache.

Credits

• Base model: deepreinforce-ai/Ornith-1.0-35B
• Abliterated weights: YuYu1015/YuYu1015-Ornith-1.0-35B-abliterated

This mirror only re-adds the standard preprocessor configs; no weights were modified.