- Libraries
- Transformers
How to use fotiecodes/Turaco-E2B-it-mt-en-wes with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "translation" 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("translation", model="fotiecodes/Turaco-E2B-it-mt-en-wes")
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 AutoProcessor, AutoModelForMultimodalLM
processor = AutoProcessor.from_pretrained("fotiecodes/Turaco-E2B-it-mt-en-wes")
model = AutoModelForMultimodalLM.from_pretrained("fotiecodes/Turaco-E2B-it-mt-en-wes", device_map="auto")
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 = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use fotiecodes/Turaco-E2B-it-mt-en-wes 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 fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
# Run inference directly in the terminal:
llama cli -hf fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
# Run inference directly in the terminal:
llama cli -hf fotiecodes/Turaco-E2B-it-mt-en-wes: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 fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf fotiecodes/Turaco-E2B-it-mt-en-wes: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 fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
Use Docker
docker model run hf.co/fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
- LM Studio
- Jan
- Ollama
How to use fotiecodes/Turaco-E2B-it-mt-en-wes with Ollama:
ollama run hf.co/fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use fotiecodes/Turaco-E2B-it-mt-en-wes with Docker Model Runner:
docker model run hf.co/fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
- Lemonade
How to use fotiecodes/Turaco-E2B-it-mt-en-wes with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/
lemonade pull fotiecodes/Turaco-E2B-it-mt-en-wes:Q8_0
Run and chat with the model
lemonade run user.Turaco-E2B-it-mt-en-wes-Q8_0
List all available models
lemonade list
- Atomic Chat
