nsfwalex Claude Opus 4.8 commited on
Commit
63b1a96
Β·
1 Parent(s): 7d87ebe

Switch assistant back to Qwen3.5-9B-Uncensored (bf16)

Browse files

VLM_MODEL_ID default -> ccharnkij/Qwen3.5-9B-Uncensored (the pre-Gemma
default). bf16 (~18.8GB, fits zero-a10g). Gemma E4B/12B kept commented for
revert. requirements unchanged -> app reload, not a full rebuild.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

Files changed (1) hide show
  1. app.py +9 -8
app.py CHANGED
@@ -152,15 +152,16 @@ print("Pipelines loaded!")
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  # -----------------------------------------------------------------------------
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  # Other models, kept for easy revert (set VLM_MODEL_ID, and VLM_LOAD_8BIT for big ones):
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  # "rodrigomt/Qwen3.5-4B-Uncensored-Aggressive" # no generation_config; needed eos pinning
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- # "ccharnkij/Qwen3.5-9B-Uncensored" # 9B Qwen3.5 VL, ~18.8 GB bf16
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  # "OpenYourMind/gemma-4-12B-it-abliterated-uncensored" # gemma4_unified, ~24GB; needs VLM_LOAD_8BIT=1 (slow)
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- # Current: gemma-4-E4B (model_type=gemma4 / Gemma4ForConditionalGeneration), multimodal,
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- # uncensored. Small/fast β€” loads full bf16 (~8 GB, fits the zero-a10g alongside the
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- # diffusion pipelines). The 12B above was accurate but too slow at 8-bit; this is the
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- # speed pick. Stop tokens are handled model-agnostically by _resolve_vlm_eos_ids()
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- # (this model ships a proper generation_config). VLM_LOAD_8BIT=1 forces bitsandbytes
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- # 8-bit (only needed for the 12B); default is bf16.
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- VLM_MODEL_ID = os.environ.get("VLM_MODEL_ID", "prithivMLmods/gemma-4-E4B-it-Uncensored-MAX")
 
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  VLM_LOAD_8BIT = os.environ.get("VLM_LOAD_8BIT", "0").lower() not in ("0", "false", "no", "")
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  print(f"Loading assistant: {VLM_MODEL_ID} (8bit={VLM_LOAD_8BIT}) ...")
 
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  # -----------------------------------------------------------------------------
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  # Other models, kept for easy revert (set VLM_MODEL_ID, and VLM_LOAD_8BIT for big ones):
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  # "rodrigomt/Qwen3.5-4B-Uncensored-Aggressive" # no generation_config; needed eos pinning
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+ # "prithivMLmods/gemma-4-E4B-it-Uncensored-MAX" # gemma4, small/fast bf16; under-rates explicit (~2)
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  # "OpenYourMind/gemma-4-12B-it-abliterated-uncensored" # gemma4_unified, ~24GB; needs VLM_LOAD_8BIT=1 (slow)
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+ # Current: 9B uncensored Qwen3.5 VL (model_type=qwen3_5 / Qwen3_5ForConditionalGeneration).
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+ # Vision-capable (image-text-to-text), bf16 (~18.8 GB β€” heaviest that still fits the
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+ # zero-a10g alongside both diffusion pipelines, verified no OOM). Thinking model
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+ # (Reasoning On/Off toggle is meaningful). Its generation_config eos is just
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+ # <|endoftext|> and omits the chat terminator <|im_end|>; _resolve_vlm_eos_ids() unions
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+ # both so stopping still works. VLM_LOAD_8BIT=1 forces bitsandbytes 8-bit (only needed
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+ # for the 12B); default is bf16.
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+ VLM_MODEL_ID = os.environ.get("VLM_MODEL_ID", "ccharnkij/Qwen3.5-9B-Uncensored")
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  VLM_LOAD_8BIT = os.environ.get("VLM_LOAD_8BIT", "0").lower() not in ("0", "false", "no", "")
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  print(f"Loading assistant: {VLM_MODEL_ID} (8bit={VLM_LOAD_8BIT}) ...")