Image-Text-to-Text
Transformers
Safetensors
Turkish
English
lora
vision-language
math
exam
yks
turkish
Instructions to use cgalabs/yks-vlm-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cgalabs/yks-vlm-lora-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="cgalabs/yks-vlm-lora-v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cgalabs/yks-vlm-lora-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use cgalabs/yks-vlm-lora-v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "cgalabs/yks-vlm-lora-v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "cgalabs/yks-vlm-lora-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/cgalabs/yks-vlm-lora-v2
- SGLang
How to use cgalabs/yks-vlm-lora-v2 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 "cgalabs/yks-vlm-lora-v2" \ --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": "cgalabs/yks-vlm-lora-v2", "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 "cgalabs/yks-vlm-lora-v2" \ --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": "cgalabs/yks-vlm-lora-v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use cgalabs/yks-vlm-lora-v2 with Docker Model Runner:
docker model run hf.co/cgalabs/yks-vlm-lora-v2
Download adapter_model.safetensors from cgalabs/yks-vlm-lora-v2: direct link, hf CLI and curl.
- Browser
- Download file 134 MB
-
https://huggingface.co/cgalabs/yks-vlm-lora-v2/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://cgalabs/yks-vlm-lora-v2/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/cgalabs/yks-vlm-lora-v2/resolve/main/adapter_model.safetensors
134 MB
- Xet hash:
- 9fd2efe96be8c444ebb91d9af3137efffa81e0995eb5937fdeadc1e117341c89
- Size of remote file:
- 134 MB
- SHA256:
- 74e6124860789860d44a05828b9c7457608ee9122580dc695f54cae43e226d9c
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