Instructions to use fevohh/GenParser-1B-v1-iter4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fevohh/GenParser-1B-v1-iter4 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fevohh/GenParser-1B-v1-iter4", dtype="auto") - llama-cpp-python
How to use fevohh/GenParser-1B-v1-iter4 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="fevohh/GenParser-1B-v1-iter4", filename="unsloth.F16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use fevohh/GenParser-1B-v1-iter4 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf fevohh/GenParser-1B-v1-iter4:F16 # Run inference directly in the terminal: llama-cli -hf fevohh/GenParser-1B-v1-iter4:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf fevohh/GenParser-1B-v1-iter4:F16 # Run inference directly in the terminal: llama-cli -hf fevohh/GenParser-1B-v1-iter4:F16
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 fevohh/GenParser-1B-v1-iter4:F16 # Run inference directly in the terminal: ./llama-cli -hf fevohh/GenParser-1B-v1-iter4:F16
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 fevohh/GenParser-1B-v1-iter4:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf fevohh/GenParser-1B-v1-iter4:F16
Use Docker
docker model run hf.co/fevohh/GenParser-1B-v1-iter4:F16
- LM Studio
- Jan
- Ollama
How to use fevohh/GenParser-1B-v1-iter4 with Ollama:
ollama run hf.co/fevohh/GenParser-1B-v1-iter4:F16
- Unsloth Studio new
How to use fevohh/GenParser-1B-v1-iter4 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 fevohh/GenParser-1B-v1-iter4 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 fevohh/GenParser-1B-v1-iter4 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for fevohh/GenParser-1B-v1-iter4 to start chatting
- Pi new
How to use fevohh/GenParser-1B-v1-iter4 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf fevohh/GenParser-1B-v1-iter4:F16
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "fevohh/GenParser-1B-v1-iter4:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use fevohh/GenParser-1B-v1-iter4 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf fevohh/GenParser-1B-v1-iter4:F16
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default fevohh/GenParser-1B-v1-iter4:F16
Run Hermes
hermes
- Docker Model Runner
How to use fevohh/GenParser-1B-v1-iter4 with Docker Model Runner:
docker model run hf.co/fevohh/GenParser-1B-v1-iter4:F16
- Lemonade
How to use fevohh/GenParser-1B-v1-iter4 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull fevohh/GenParser-1B-v1-iter4:F16
Run and chat with the model
lemonade run user.GenParser-1B-v1-iter4-F16
List all available models
lemonade list
Contents:
decent model (q8), surpasses iter1 and 2 (gna ignore iter3, completely useless) in terms of extracting more items from user listing, but is still prone to extracting the same item mentioned repeatedly. still not as good as 3b, but fast (4x faster, 69t/s in 1b and 17t/s in 3b running on 3050 laptop) and reliable enough to perform simple extraction for a listing with less than 5 items and no world name
Uploaded model
- Developed by: fevohh
- License: apache-2.0
- Finetuned from model : unsloth/Llama-3.2-1B-Instruct-unsloth-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
- Downloads last month
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8-bit
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Model tree for fevohh/GenParser-1B-v1-iter4
Base model
meta-llama/Llama-3.2-1B-Instruct
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("fevohh/GenParser-1B-v1-iter4", dtype="auto")