Transformers
GGUF
English
Chinese
WebWorld
web-agent
world-model
simulator
browser
a11y
html
xml
markdown
long-horizon
long-context
synthetic-trajectories
instruction-tuning
conversational
Instructions to use mradermacher/WebWorld-8B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mradermacher/WebWorld-8B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mradermacher/WebWorld-8B-GGUF", dtype="auto") - llama-cpp-python
How to use mradermacher/WebWorld-8B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mradermacher/WebWorld-8B-GGUF", filename="WebWorld-8B.IQ4_XS.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 mradermacher/WebWorld-8B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mradermacher/WebWorld-8B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/WebWorld-8B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mradermacher/WebWorld-8B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mradermacher/WebWorld-8B-GGUF: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 mradermacher/WebWorld-8B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mradermacher/WebWorld-8B-GGUF: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 mradermacher/WebWorld-8B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mradermacher/WebWorld-8B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mradermacher/WebWorld-8B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use mradermacher/WebWorld-8B-GGUF with Ollama:
ollama run hf.co/mradermacher/WebWorld-8B-GGUF:Q4_K_M
- Unsloth Studio new
How to use mradermacher/WebWorld-8B-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 mradermacher/WebWorld-8B-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 mradermacher/WebWorld-8B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mradermacher/WebWorld-8B-GGUF to start chatting
- Pi new
How to use mradermacher/WebWorld-8B-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mradermacher/WebWorld-8B-GGUF:Q4_K_M
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": "mradermacher/WebWorld-8B-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mradermacher/WebWorld-8B-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf mradermacher/WebWorld-8B-GGUF:Q4_K_M
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 mradermacher/WebWorld-8B-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use mradermacher/WebWorld-8B-GGUF with Docker Model Runner:
docker model run hf.co/mradermacher/WebWorld-8B-GGUF:Q4_K_M
- Lemonade
How to use mradermacher/WebWorld-8B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mradermacher/WebWorld-8B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.WebWorld-8B-GGUF-Q4_K_M
List all available models
lemonade list
auto-patch README.md
Browse files
README.md
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@@ -42,7 +42,7 @@ static quants of https://huggingface.co/Qwen/WebWorld-8B
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#WebWorld-8B-GGUF).***
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weighted/imatrix quants
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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| Link | Type | Size/GB | Notes |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q3_K_M.gguf) | Q3_K_M | 4.2 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q4_K_S.gguf) | Q4_K_S | 4.9 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q5_K_S.gguf) | Q5_K_S | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.f16.gguf) | f16 | 16.5 | 16 bpw, overkill |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#WebWorld-8B-GGUF).***
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/WebWorld-8B-i1-GGUF
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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| Link | Type | Size/GB | Notes |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q2_K.gguf) | Q2_K | 3.4 | |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q3_K_S.gguf) | Q3_K_S | 3.9 | |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q3_K_M.gguf) | Q3_K_M | 4.2 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q3_K_L.gguf) | Q3_K_L | 4.5 | |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.IQ4_XS.gguf) | IQ4_XS | 4.7 | |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q4_K_S.gguf) | Q4_K_S | 4.9 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q4_K_M.gguf) | Q4_K_M | 5.1 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q5_K_S.gguf) | Q5_K_S | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q5_K_M.gguf) | Q5_K_M | 6.0 | |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q6_K.gguf) | Q6_K | 6.8 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.Q8_0.gguf) | Q8_0 | 8.8 | fast, best quality |
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| [GGUF](https://huggingface.co/mradermacher/WebWorld-8B-GGUF/resolve/main/WebWorld-8B.f16.gguf) | f16 | 16.5 | 16 bpw, overkill |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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