Instructions to use itod/UAE-Large-V1-Q8_0-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use itod/UAE-Large-V1-Q8_0-GGUF with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("itod/UAE-Large-V1-Q8_0-GGUF") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use itod/UAE-Large-V1-Q8_0-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("itod/UAE-Large-V1-Q8_0-GGUF", device_map="auto") - Transformers.js
How to use itod/UAE-Large-V1-Q8_0-GGUF with Transformers.js:
// ⚠️ Unknown pipeline tag
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use itod/UAE-Large-V1-Q8_0-GGUF 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 itod/UAE-Large-V1-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf itod/UAE-Large-V1-Q8_0-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf itod/UAE-Large-V1-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: llama cli -hf itod/UAE-Large-V1-Q8_0-GGUF: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 itod/UAE-Large-V1-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf itod/UAE-Large-V1-Q8_0-GGUF: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 itod/UAE-Large-V1-Q8_0-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf itod/UAE-Large-V1-Q8_0-GGUF:Q8_0
Use Docker
docker model run hf.co/itod/UAE-Large-V1-Q8_0-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use itod/UAE-Large-V1-Q8_0-GGUF with Ollama:
ollama run hf.co/itod/UAE-Large-V1-Q8_0-GGUF:Q8_0
- Unsloth Studio
How to use itod/UAE-Large-V1-Q8_0-GGUF 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 itod/UAE-Large-V1-Q8_0-GGUF 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 itod/UAE-Large-V1-Q8_0-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for itod/UAE-Large-V1-Q8_0-GGUF to start chatting
- Docker Model Runner
How to use itod/UAE-Large-V1-Q8_0-GGUF with Docker Model Runner:
docker model run hf.co/itod/UAE-Large-V1-Q8_0-GGUF:Q8_0
- Lemonade
How to use itod/UAE-Large-V1-Q8_0-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull itod/UAE-Large-V1-Q8_0-GGUF:Q8_0
Run and chat with the model
lemonade run user.UAE-Large-V1-Q8_0-GGUF-Q8_0
List all available models
lemonade list
- Atomic Chat
itod/UAE-Large-V1-Q8_0-GGUF
This model was converted to GGUF format from WhereIsAI/UAE-Large-V1 using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama --hf-repo itod/UAE-Large-V1-Q8_0-GGUF --hf-file uae-large-v1-q8_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo itod/UAE-Large-V1-Q8_0-GGUF --hf-file uae-large-v1-q8_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./main --hf-repo itod/UAE-Large-V1-Q8_0-GGUF --hf-file uae-large-v1-q8_0.gguf -p "The meaning to life and the universe is"
or
./server --hf-repo itod/UAE-Large-V1-Q8_0-GGUF --hf-file uae-large-v1-q8_0.gguf -c 2048
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Base model
WhereIsAI/UAE-Large-V1Spaces using itod/UAE-Large-V1-Q8_0-GGUF 11
Evaluation results
- accuracy on MTEB AmazonCounterfactualClassification (en)test set self-reported75.552
- ap on MTEB AmazonCounterfactualClassification (en)test set self-reported38.264
- f1 on MTEB AmazonCounterfactualClassification (en)test set self-reported69.410
- accuracy on MTEB AmazonPolarityClassificationtest set self-reported92.843
- ap on MTEB AmazonPolarityClassificationtest set self-reported89.576
- f1 on MTEB AmazonPolarityClassificationtest set self-reported92.826
- accuracy on MTEB AmazonReviewsClassification (en)test set self-reported48.292
- f1 on MTEB AmazonReviewsClassification (en)test set self-reported47.903