Text Generation
Transformers
Safetensors
English
gemma4_unified
image-text-to-text
oncology
medical
pancreatic-cancer
gemma
sft
research
Instructions to use Joesh1/onca-2.0-12b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joesh1/onca-2.0-12b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Joesh1/onca-2.0-12b")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Joesh1/onca-2.0-12b") model = AutoModelForMultimodalLM.from_pretrained("Joesh1/onca-2.0-12b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Joesh1/onca-2.0-12b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Joesh1/onca-2.0-12b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Joesh1/onca-2.0-12b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Joesh1/onca-2.0-12b
- SGLang
How to use Joesh1/onca-2.0-12b 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 "Joesh1/onca-2.0-12b" \ --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": "Joesh1/onca-2.0-12b", "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 "Joesh1/onca-2.0-12b" \ --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": "Joesh1/onca-2.0-12b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Joesh1/onca-2.0-12b with Docker Model Runner:
docker model run hf.co/Joesh1/onca-2.0-12b
File size: 1,382 Bytes
e6ef575 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | {
"audio_ms_per_token": 40,
"audio_seq_length": 750,
"feature_extractor": {
"audio_samples_per_token": 640,
"feature_extractor_type": "Gemma4UnifiedAudioFeatureExtractor",
"feature_size": 640,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000
},
"image_processor": {
"do_convert_rgb": true,
"do_normalize": false,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.0,
0.0,
0.0
],
"image_processor_type": "Gemma4UnifiedImageProcessor",
"image_std": [
1.0,
1.0,
1.0
],
"max_soft_tokens": 280,
"patch_size": 16,
"pooling_kernel_size": 3,
"resample": 3,
"rescale_factor": 0.00392156862745098
},
"image_seq_length": 280,
"processor_class": "Gemma4UnifiedProcessor",
"video_processor": {
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"do_sample_frames": true,
"image_mean": [
0.0,
0.0,
0.0
],
"image_std": [
1.0,
1.0,
1.0
],
"max_soft_tokens": 70,
"num_frames": 32,
"patch_size": 16,
"pooling_kernel_size": 3,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"return_metadata": false,
"video_processor_type": "Gemma4UnifiedVideoProcessor"
}
}
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