pixtral-12b

121.6K
103
license:apache-2.0
by
mistral-labs
Image Model
OTHER
12B params
Good
122K downloads
Production-ready
Try on Hugging FaceAdd to Compare
Edge AI:
Mobile
Laptop
Server
27GB+ RAM
Mobile
Laptop
Server
Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
12GB+ RAM

Code Examples

Model Card for Model IDpythontransformers
from PIL import Image
from transformers import AutoProcessor, LlavaForConditionalGeneration
model_id = "mistral-community/pixtral-12b"
model = LlavaForConditionalGeneration.from_pretrained(model_id)
processor = AutoProcessor.from_pretrained(model_id)

IMG_URLS = [
"https://picsum.photos/id/237/400/300", 
"https://picsum.photos/id/231/200/300", 
"https://picsum.photos/id/27/500/500",
"https://picsum.photos/id/17/150/600",
]
PROMPT = "<s>[INST]Describe the images.\n[IMG][IMG][IMG][IMG][/INST]"

inputs = processor(text=PROMPT, images=IMG_URLS, return_tensors="pt").to("cuda")
generate_ids = model.generate(**inputs, max_new_tokens=500)
output = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
python
chat = [
    {
      "role": "user", "content": [
        {"type": "text", "content": "Can this animal"}, 
        {"type": "image", "url": url_dog}, 
        {"type": "text", "content": "live here?"}, 
        {"type": "image", "url" : url_mountain}
      ]
    }
]

inputs = processor.apply_chat_template(chat, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors"pt").to(model.device)
generate_ids = model.generate(**inputs, max_new_tokens=500)
output = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]

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