Image-Text-to-Text
Transformers
Safetensors
paligemma
text-generation-inference
8-bit precision
bitsandbytes
Instructions to use Pushpendra817/Xtraektor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pushpendra817/Xtraektor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Pushpendra817/Xtraektor")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Pushpendra817/Xtraektor") model = AutoModelForMultimodalLM.from_pretrained("Pushpendra817/Xtraektor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Pushpendra817/Xtraektor with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Pushpendra817/Xtraektor" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pushpendra817/Xtraektor", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Pushpendra817/Xtraektor
- SGLang
How to use Pushpendra817/Xtraektor 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 "Pushpendra817/Xtraektor" \ --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": "Pushpendra817/Xtraektor", "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 "Pushpendra817/Xtraektor" \ --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": "Pushpendra817/Xtraektor", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Pushpendra817/Xtraektor with Docker Model Runner:
docker model run hf.co/Pushpendra817/Xtraektor
Download config.json from Pushpendra817/Xtraektor: direct link, hf CLI and curl.
- Browser
- Download file 1.5 kB
-
https://huggingface.co/Pushpendra817/Xtraektor/resolve/main/config.json
- Command line
-
hf download hf://Pushpendra817/Xtraektor/config.json
-
curl -L -o config.json https://huggingface.co/Pushpendra817/Xtraektor/resolve/main/config.json
1.5 kB
| { | |
| "_name_or_path": "google/paligemma-3b-mix-224", | |
| "architectures": [ | |
| "PaliGemmaForConditionalGeneration" | |
| ], | |
| "bos_token_id": 2, | |
| "eos_token_id": 1, | |
| "hidden_size": 2048, | |
| "ignore_index": -100, | |
| "image_token_index": 257152, | |
| "model_type": "paligemma", | |
| "pad_token_id": 0, | |
| "projection_dim": 2048, | |
| "quantization_config": { | |
| "_load_in_4bit": false, | |
| "_load_in_8bit": true, | |
| "bnb_4bit_compute_dtype": "float32", | |
| "bnb_4bit_quant_storage": "uint8", | |
| "bnb_4bit_quant_type": "fp4", | |
| "bnb_4bit_use_double_quant": false, | |
| "llm_int8_enable_fp32_cpu_offload": false, | |
| "llm_int8_has_fp16_weight": false, | |
| "llm_int8_skip_modules": null, | |
| "llm_int8_threshold": 6.0, | |
| "load_in_4bit": false, | |
| "load_in_8bit": true, | |
| "quant_method": "bitsandbytes" | |
| }, | |
| "text_config": { | |
| "hidden_size": 2048, | |
| "intermediate_size": 16384, | |
| "model_type": "gemma", | |
| "num_attention_heads": 8, | |
| "num_hidden_layers": 18, | |
| "num_image_tokens": 256, | |
| "num_key_value_heads": 1, | |
| "torch_dtype": "float32", | |
| "vocab_size": 257216 | |
| }, | |
| "torch_dtype": "float16", | |
| "transformers_version": "4.42.4", | |
| "vision_config": { | |
| "hidden_size": 1152, | |
| "intermediate_size": 4304, | |
| "model_type": "siglip_vision_model", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 27, | |
| "num_image_tokens": 256, | |
| "patch_size": 14, | |
| "projection_dim": 2048, | |
| "projector_hidden_act": "gelu_fast", | |
| "vision_use_head": false | |
| }, | |
| "vocab_size": 257216 | |
| } | |