Image-Text-to-Text
Transformers
Safetensors
GGUF
English
mistral
text-generation
art
medical
biology
code
chemistry
conversational
custom_code
text-generation-inference
Instructions to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="LeroyDyer/SpydazWeb_AI_ImageText_Text_Project", 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/SpydazWeb_AI_ImageText_Text_Project", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("LeroyDyer/SpydazWeb_AI_ImageText_Text_Project", 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]:])) - llama-cpp-python
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="LeroyDyer/SpydazWeb_AI_ImageText_Text_Project", filename="mixtral_ai_vision-instruct_x.q8_0.gguf", )
llm.create_chat_completion( 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" } } ] } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0 # Run inference directly in the terminal: llama cli -hf LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0 # Run inference directly in the terminal: llama cli -hf LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0
Use Docker
docker model run hf.co/LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0
- LM Studio
- Jan
- vLLM
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LeroyDyer/SpydazWeb_AI_ImageText_Text_Project" # 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/SpydazWeb_AI_ImageText_Text_Project", "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/SpydazWeb_AI_ImageText_Text_Project:Q8_0
- SGLang
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project 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/SpydazWeb_AI_ImageText_Text_Project" \ --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/SpydazWeb_AI_ImageText_Text_Project", "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/SpydazWeb_AI_ImageText_Text_Project" \ --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/SpydazWeb_AI_ImageText_Text_Project", "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" } } ] } ] }' - Ollama
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with Ollama:
ollama run hf.co/LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0
- Unsloth Studio
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for LeroyDyer/SpydazWeb_AI_ImageText_Text_Project to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for LeroyDyer/SpydazWeb_AI_ImageText_Text_Project to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for LeroyDyer/SpydazWeb_AI_ImageText_Text_Project to start chatting
- Atomic Chat new
- Docker Model Runner
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with Docker Model Runner:
docker model run hf.co/LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0
- Lemonade
How to use LeroyDyer/SpydazWeb_AI_ImageText_Text_Project with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull LeroyDyer/SpydazWeb_AI_ImageText_Text_Project:Q8_0
Run and chat with the model
lemonade run user.SpydazWeb_AI_ImageText_Text_Project-Q8_0
List all available models
lemonade list
| { | |
| "aspect_ratio_setting": "anyres", | |
| "crop_size": { | |
| "height": 336, | |
| "width": 336 | |
| }, | |
| "do_center_crop": true, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_grid_pinpoints": [ | |
| [ | |
| 336, | |
| 672 | |
| ], | |
| [ | |
| 672, | |
| 336 | |
| ], | |
| [ | |
| 672, | |
| 672 | |
| ], | |
| [ | |
| 1008, | |
| 336 | |
| ], | |
| [ | |
| 336, | |
| 1008 | |
| ] | |
| ], | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "LlavaNextImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "processor_class": "LlavaNextProcessor", | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 336 | |
| } | |
| } | |