Cambrian-S-7B

Name: Cambrian-S-7B
Author: nyu-visionx

7.0B

1 language

license:apache-2.0

nyu-visionx

Image Model

OTHER

7B params

New

13 downloads

Early-stage

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

16GB+ RAM

Mobile

Laptop

Server

Quick Summary

Authors: Shusheng Yang, Jihan Yang, Pinzhi Huang†, Ellis Brown†, et al.

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

7GB+ RAM

Code Examples

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Usagepython

from cambrian.model.builder import load_pretrained_model
from cambrian.mm_utils import process_images, tokenizer_image_token
from cambrian.conversation import conv_templates

model_path = "nyu-visionx/Cambrian-S-7B"
tokenizer, model, image_processor, _ = load_pretrained_model(model_path, None, "cambrian-s-7b", device_map="cuda")

# Process image/video
conv = conv_templates["qwen_2"].copy()
conv.append_message(conv.roles[0], "<image>\nWhat objects are in this scene?")
conv.append_message(conv.roles[1], None)
prompt = conv.get_prompt()

# Generate
output_ids = model.generate(input_ids, images=image_tensor, image_sizes=image_sizes)

Deploy This Model

Production-ready deployment in minutes

Together.ai

Instant API access to this model

Fastest API

Production-ready inference API. Start free, scale to millions.

Try Free API

Replicate

One-click model deployment

Easiest Setup

Run models in the cloud with simple API. No DevOps required.

Deploy Now

Disclosure: We may earn a commission from these partners. This helps keep LLMYourWay free.