Instructions to use LeroyDyer/Mixtral_AI_CyberVision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LeroyDyer/Mixtral_AI_CyberVision with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-text-to-text", model="LeroyDyer/Mixtral_AI_CyberVision", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LeroyDyer/Mixtral_AI_CyberVision", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("LeroyDyer/Mixtral_AI_CyberVision", trust_remote_code=True)
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use LeroyDyer/Mixtral_AI_CyberVision with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LeroyDyer/Mixtral_AI_CyberVision"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LeroyDyer/Mixtral_AI_CyberVision",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/LeroyDyer/Mixtral_AI_CyberVision

SGLang

How to use LeroyDyer/Mixtral_AI_CyberVision 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 "LeroyDyer/Mixtral_AI_CyberVision" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LeroyDyer/Mixtral_AI_CyberVision",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "LeroyDyer/Mixtral_AI_CyberVision" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LeroyDyer/Mixtral_AI_CyberVision",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use LeroyDyer/Mixtral_AI_CyberVision with Docker Model Runner:
```
docker model run hf.co/LeroyDyer/Mixtral_AI_CyberVision
```

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

LeroyDyer/Mixtral_AI_Vision_128k

This model is also a Vision model with 128k context window:

To be further refined! Working!

VISION+ Language Model


If you want to use vision functionality:

Make sure you are using the latest version of KoboldCpp.
To use the multimodal capabilities of this model, such as vision, you also need to load the specified mmproj file, you can get it here.

https://huggingface.co/LeroyDyer/Mixtral_AI_Vision_128k/blob/main/mmproj-model-f16.gguf

You can load the mmproj by using the corresponding section in the interface:


KoboldCpp now supports Vision via Multimodal Projectors (aka LLaVA), allowing it to perceive and react to images! Load a suitable --mmproj file or select it in the GUI launcher to use vision capabilities. (Not working on Vulkan)
Note: This is NOT limited to only LLaVA models, any compatible model of the same size and architecture can gain vision capabilities!
Simply grab a 200mb mmproj file for your architecture here,

 https://huggingface.co/koboldcpp/mmproj

load it with --mmproj and stick it into your favorite compatible model, and it will be able to see images as well!

Merge Details

Merge Method

This model was merged using the linear merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

Downloads last month: -

Safetensors

Model size

7B params

Tensor type

F16

Model tree for LeroyDyer/Mixtral_AI_CyberVision

Base model

ChaoticNeutrals/Eris_PrimeV3-Vision-7B

Quantized

(4)

this model

Collections including LeroyDyer/Mixtral_AI_CyberVision

Paper for LeroyDyer/Mixtral_AI_CyberVision

Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Paper • 2203.05482 • Published Mar 10, 2022 • 8