Instructions to use OddTheGreat/Comet_12B_V.7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OddTheGreat/Comet_12B_V.7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OddTheGreat/Comet_12B_V.7")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("OddTheGreat/Comet_12B_V.7") model = AutoModelForMultimodalLM.from_pretrained("OddTheGreat/Comet_12B_V.7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OddTheGreat/Comet_12B_V.7 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OddTheGreat/Comet_12B_V.7" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OddTheGreat/Comet_12B_V.7", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OddTheGreat/Comet_12B_V.7
- SGLang
How to use OddTheGreat/Comet_12B_V.7 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 "OddTheGreat/Comet_12B_V.7" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OddTheGreat/Comet_12B_V.7", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "OddTheGreat/Comet_12B_V.7" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OddTheGreat/Comet_12B_V.7", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OddTheGreat/Comet_12B_V.7 with Docker Model Runner:
docker model run hf.co/OddTheGreat/Comet_12B_V.7
merges
This is a merge of pre-trained language models
Goal of this merge was to create a good, non-robotic 12b gemma3 model for roleplay and creative purposes.
Model is quite good for 12b, is context attentive, good at following instructions and is creative enough.
It stays in character and writes quite nice, but prone for long, detailed responses (400-700 tokens) and still had some gemma slop.
RU is supported, in assistant role is good, but not tested in RP.
Vision works, but has censorship problems (5 of 10 are refusals) with default gemma 12b mmproj. (maybe skill issue, i don't use vision for nsfw)
Tested on t1.04, XTC off or 0.1 0.15.
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