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Kleva-ai
/
ItaLegalEmb_v2

Sentence Similarity
sentence-transformers
Safetensors
GGUF
xlm-roberta
feature-extraction
Italian
text-embeddings-inference
Model card Files Files and versions
xet
Community
4

Instructions to use Kleva-ai/ItaLegalEmb_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Kleva-ai/ItaLegalEmb_v2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Kleva-ai/ItaLegalEmb_v2")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • llama-cpp-python

    How to use Kleva-ai/ItaLegalEmb_v2 with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="Kleva-ai/ItaLegalEmb_v2",
    	filename="ItaLegalEmb_v2.gguf",
    )
    
    output = llm(
    	"Once upon a time,",
    	max_tokens=512,
    	echo=True
    )
    print(output)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • llama.cpp

    How to use Kleva-ai/ItaLegalEmb_v2 with llama.cpp:

    Install from brew
    brew install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf Kleva-ai/ItaLegalEmb_v2
    # Run inference directly in the terminal:
    llama-cli -hf Kleva-ai/ItaLegalEmb_v2
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf Kleva-ai/ItaLegalEmb_v2
    # Run inference directly in the terminal:
    llama-cli -hf Kleva-ai/ItaLegalEmb_v2
    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 Kleva-ai/ItaLegalEmb_v2
    # Run inference directly in the terminal:
    ./llama-cli -hf Kleva-ai/ItaLegalEmb_v2
    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 Kleva-ai/ItaLegalEmb_v2
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf Kleva-ai/ItaLegalEmb_v2
    Use Docker
    docker model run hf.co/Kleva-ai/ItaLegalEmb_v2
  • LM Studio
  • Jan
  • Ollama

    How to use Kleva-ai/ItaLegalEmb_v2 with Ollama:

    ollama run hf.co/Kleva-ai/ItaLegalEmb_v2
  • Unsloth Studio new

    How to use Kleva-ai/ItaLegalEmb_v2 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 Kleva-ai/ItaLegalEmb_v2 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 Kleva-ai/ItaLegalEmb_v2 to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for Kleva-ai/ItaLegalEmb_v2 to start chatting
  • Docker Model Runner

    How to use Kleva-ai/ItaLegalEmb_v2 with Docker Model Runner:

    docker model run hf.co/Kleva-ai/ItaLegalEmb_v2
  • Lemonade

    How to use Kleva-ai/ItaLegalEmb_v2 with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull Kleva-ai/ItaLegalEmb_v2
    Run and chat with the model
    lemonade run user.ItaLegalEmb_v2-{{QUANT_TAG}}
    List all available models
    lemonade list

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