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How to use LeroyDyer/SpydazWebAI_Image_Projectors with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "image-to-text" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline
pipe = pipeline("image-to-text", model="LeroyDyer/SpydazWebAI_Image_Projectors") # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("LeroyDyer/SpydazWebAI_Image_Projectors", dtype="auto")How to use LeroyDyer/SpydazWebAI_Image_Projectors with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="LeroyDyer/SpydazWebAI_Image_Projectors", filename="Mixtral_LLAVA_7b.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
How to use LeroyDyer/SpydazWebAI_Image_Projectors with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0 # Run inference directly in the terminal: llama-cli -hf LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0 # Run inference directly in the terminal: llama-cli -hf LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0
# 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/SpydazWebAI_Image_Projectors:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0
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/SpydazWebAI_Image_Projectors:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0
docker model run hf.co/LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0
How to use LeroyDyer/SpydazWebAI_Image_Projectors with Ollama:
ollama run hf.co/LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0
How to use LeroyDyer/SpydazWebAI_Image_Projectors with Unsloth Studio:
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/SpydazWebAI_Image_Projectors to start chatting
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/SpydazWebAI_Image_Projectors to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for LeroyDyer/SpydazWebAI_Image_Projectors to start chatting
How to use LeroyDyer/SpydazWebAI_Image_Projectors with Docker Model Runner:
docker model run hf.co/LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0
How to use LeroyDyer/SpydazWebAI_Image_Projectors with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull LeroyDyer/SpydazWebAI_Image_Projectors:Q4_0
lemonade run user.SpydazWebAI_Image_Projectors-Q4_0
lemonade list
output = llm(
"Once upon a time,",
max_tokens=512,
echo=True
)
print(output)These are the extra files to be added to your model space to enable for the modle to become a Image to text model hence ts that easy to becoem multimodel
https://github.com/spydaz
We're not able to determine the quantization variants.
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="LeroyDyer/SpydazWebAI_Image_Projectors", filename="", )