Instructions to use anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF", filename="Eve-2-MoE-NanoSQL-272M-Q4_K_M.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 anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf anthonym21/Eve-2-MoE-NanoSQL-272M-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 anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf anthonym21/Eve-2-MoE-NanoSQL-272M-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 anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf anthonym21/Eve-2-MoE-NanoSQL-272M-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 anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M
Use Docker
docker model run hf.co/anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF with Ollama:
ollama run hf.co/anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M
- Unsloth Studio new
How to use anthonym21/Eve-2-MoE-NanoSQL-272M-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 anthonym21/Eve-2-MoE-NanoSQL-272M-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 anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF to start chatting
- Docker Model Runner
How to use anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF with Docker Model Runner:
docker model run hf.co/anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M
- Lemonade
How to use anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull anthonym21/Eve-2-MoE-NanoSQL-272M-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Eve-2-MoE-NanoSQL-272M-GGUF-Q4_K_M
List all available models
lemonade list
Add GGUF quantizations (Q8_0, Q4_K_M)
Browse files- .gitattributes +2 -0
- Eve-2-MoE-NanoSQL-272M-Q4_K_M.gguf +3 -0
- Eve-2-MoE-NanoSQL-272M-Q8_0.gguf +3 -0
- README.md +46 -0
.gitattributes
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---
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base_model: anthonym21/Eve-2-MoE-NanoSQL-272M
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tags:
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- gguf
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- quantized
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- moe
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- eve-2
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license: apache-2.0
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---
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# Eve-2-MoE-NanoSQL-272M - GGUF
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GGUF quantizations of [anthonym21/Eve-2-MoE-NanoSQL-272M](https://huggingface.co/anthonym21/Eve-2-MoE-NanoSQL-272M).
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## Quantization Variants
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| Quantization | Filename | Size |
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|---|---|---|
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| Q8_0 | Eve-2-MoE-NanoSQL-272M-Q8_0.gguf | 290.9 MB |
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| Q4_K_M | Eve-2-MoE-NanoSQL-272M-Q4_K_M.gguf | 189.5 MB |
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## Usage with Ollama
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```bash
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ollama run anthonym21/eve-2-moe-nanosql-272m
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```
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## Usage with llama.cpp
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```bash
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llama-cli -m Eve-2-MoE-NanoSQL-272M-Q4_K_M.gguf -p "Your prompt here"
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```
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## Architecture
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- **Type**: DeepSeek-style Mixture of Experts (MoE)
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- **Parameters**: 272M total
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- **Layers**: 12
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- **Hidden dim**: 512
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- **Experts**: 8 routed (top-2) + 1 shared per layer
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- **Context**: 2048 tokens
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- **Tokenizer**: GPT-2
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## Parent Model
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This is a quantized version of [anthonym21/Eve-2-MoE-NanoSQL-272M](https://huggingface.co/anthonym21/Eve-2-MoE-NanoSQL-272M).
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