Image-Text-to-Text
Transformers
Safetensors
English
Chinese
gemma3
unsloth
fine tune
heretic
uncensored
abliterated
multi-stage tuned.
all use cases
coder
creative
creative writing
fiction writing
plot generation
sub-plot generation
story generation
scene continue
storytelling
fiction story
science fiction
romance
all genres
story
writing
vivid prosing
vivid writing
fiction
roleplaying
bfloat16
conversational
text-generation-inference
Instructions to use DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking") model = AutoModelForMultimodalLM.from_pretrained("DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking
- SGLang
How to use DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Unsloth Studio
How to use DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking", max_seq_length=2048, ) - Docker Model Runner
How to use DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking with Docker Model Runner:
docker model run hf.co/DavidAU/gemma-3-it-vl-40B-Gemini-Heretic-Uncensored-Thinking
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- chat_template.jinja +47 -0
- config.json +42 -0
- model-00001-of-00017.safetensors +3 -0
- model-00002-of-00017.safetensors +3 -0
- model-00003-of-00017.safetensors +3 -0
- model-00004-of-00017.safetensors +3 -0
- model-00005-of-00017.safetensors +3 -0
- model-00006-of-00017.safetensors +3 -0
- model-00007-of-00017.safetensors +3 -0
- model-00008-of-00017.safetensors +3 -0
- model-00009-of-00017.safetensors +3 -0
- model-00010-of-00017.safetensors +3 -0
- model-00011-of-00017.safetensors +3 -0
- model-00012-of-00017.safetensors +3 -0
- model-00013-of-00017.safetensors +3 -0
- model-00014-of-00017.safetensors +3 -0
- model-00015-of-00017.safetensors +3 -0
- model-00016-of-00017.safetensors +3 -0
- model-00017-of-00017.safetensors +3 -0
- model.safetensors.index.json +0 -0
- preprocessor_config.json +29 -0
- processor_config.json +29 -0
- special_tokens_map.json +33 -0
- tokenizer.json +3 -0
- tokenizer.model +3 -0
- tokenizer_config.json +0 -0
.gitattributes
CHANGED
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@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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chat_template.jinja
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{{ bos_token }}
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{%- if messages[0]['role'] == 'system' -%}
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{%- if messages[0]['content'] is string -%}
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{%- set first_user_prefix = messages[0]['content'] + '
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' -%}
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{%- else -%}
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{%- set first_user_prefix = messages[0]['content'][0]['text'] + '
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' -%}
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{%- endif -%}
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{%- set loop_messages = messages[1:] -%}
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{%- else -%}
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{%- set first_user_prefix = "" -%}
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{%- set loop_messages = messages -%}
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{%- endif -%}
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{%- for message in loop_messages -%}
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{%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
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{{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
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{%- endif -%}
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{%- if (message['role'] == 'assistant') -%}
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{%- set role = "model" -%}
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{%- else -%}
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{%- set role = message['role'] -%}
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{%- endif -%}
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{{ '<start_of_turn>' + role + '
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' + (first_user_prefix if loop.first else "") }}
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{%- if message['content'] is string -%}
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{{ message['content'] | trim }}
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{%- elif message['content'] is iterable -%}
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{%- for item in message['content'] -%}
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{%- if item['type'] == 'image' -%}
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{{ '<start_of_image>' }}
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{%- elif item['type'] == 'text' -%}
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{{ item['text'] | trim }}
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{%- endif -%}
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{%- endfor -%}
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{%- else -%}
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{{ raise_exception("Invalid content type") }}
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{%- endif -%}
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{{ '<end_of_turn>
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' }}
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{%- endfor -%}
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{%- if add_generation_prompt -%}
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{{'<start_of_turn>model
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'}}
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{%- endif -%}
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config.json
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{
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"architectures": [
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"Gemma3ForConditionalGeneration"
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],
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"boi_token_index": 255999,
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"eoi_token_index": 256000,
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"eos_token_id": [
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],
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"image_token_index": 262144,
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"initializer_range": 0.02,
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"mm_tokens_per_image": 256,
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"model_type": "gemma3",
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"text_config": {
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"head_dim": 128,
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"hidden_size": 5376,
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"intermediate_size": 21504,
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"model_type": "gemma3_text",
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"num_attention_heads": 32,
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"num_hidden_layers": 94,
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"num_key_value_heads": 16,
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"query_pre_attn_scalar": 168,
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"rope_scaling": {
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"factor": 8.0,
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"rope_type": "linear"
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},
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"sliding_window": 1024
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},
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"torch_dtype": "bfloat16",
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"transformers_version": "4.50.0.dev0",
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"vision_config": {
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"hidden_size": 1152,
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"image_size": 896,
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"intermediate_size": 4304,
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"model_type": "siglip_vision_model",
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"num_attention_heads": 16,
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"num_hidden_layers": 27,
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"patch_size": 14,
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"vision_use_head": false
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}
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model-00015-of-00017.safetensors
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model-00016-of-00017.safetensors
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model-00017-of-00017.safetensors
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model.safetensors.index.json
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preprocessor_config.json
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processor_config.json
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special_tokens_map.json
ADDED
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| 14 |
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| 17 |
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| 19 |
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| 21 |
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| 22 |
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| 25 |
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| 26 |
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| 27 |
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| 28 |
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| 29 |
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| 30 |
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| 31 |
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|
| 32 |
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}
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| 33 |
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}
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tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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tokenizer.model
ADDED
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tokenizer_config.json
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