Instructions to use Able2/umt5-xxl-encode-only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Able2/umt5-xxl-encode-only with Transformers:

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Able2/umt5-xxl-encode-only")
model = AutoModelForSeq2SeqLM.from_pretrained("Able2/umt5-xxl-encode-only", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Able2/umt5-xxl-encode-only 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 Able2/umt5-xxl-encode-only:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Able2/umt5-xxl-encode-only:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Able2/umt5-xxl-encode-only:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Able2/umt5-xxl-encode-only:Q4_K_M

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 Able2/umt5-xxl-encode-only:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Able2/umt5-xxl-encode-only:Q4_K_M

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 Able2/umt5-xxl-encode-only:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Able2/umt5-xxl-encode-only:Q4_K_M

Use Docker

docker model run hf.co/Able2/umt5-xxl-encode-only:Q4_K_M

LM Studio
Jan
Ollama
How to use Able2/umt5-xxl-encode-only with Ollama:
```
ollama run hf.co/Able2/umt5-xxl-encode-only:Q4_K_M
```

Unsloth Studio

How to use Able2/umt5-xxl-encode-only 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 Able2/umt5-xxl-encode-only 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 Able2/umt5-xxl-encode-only to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Able2/umt5-xxl-encode-only to start chatting

Docker Model Runner
How to use Able2/umt5-xxl-encode-only with Docker Model Runner:
```
docker model run hf.co/Able2/umt5-xxl-encode-only:Q4_K_M
```

Lemonade

How to use Able2/umt5-xxl-encode-only with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Able2/umt5-xxl-encode-only:Q4_K_M

Run and chat with the model

lemonade run user.umt5-xxl-encode-only-Q4_K_M

List all available models

lemonade list

Atomic Chat

An encoder only version of google's umt5-xxl model, mainly used as text encoder for image or video generation models.

Original Repo: https://huggingface.co/google/umt5-xxl
Quantized version: https://huggingface.co/Able2/umt5-xxl-encode-only-gguf

Downloads last month: 50

Safetensors

Model size

6B params

Tensor type

F32

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Model tree for Able2/umt5-xxl-encode-only

Base model

google/umt5-xxl

Quantized

(6)

this model

Quantizations

2 models