Text Generation
Safetensors
GGUF
Rust
English
Vietnamese
dioxus
accessibility
wcag
fine-tuned
raft
code
server-functions
qwen3
family-hub
scoped-css
syncstore
conversational
Instructions to use rockypod/neotoi-coder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use rockypod/neotoi-coder with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="rockypod/neotoi-coder", filename="neotoi-coder-v1-q4_k_m_final.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use rockypod/neotoi-coder with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rockypod/neotoi-coder:Q4_K_M # Run inference directly in the terminal: llama-cli -hf rockypod/neotoi-coder:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf rockypod/neotoi-coder:Q4_K_M # Run inference directly in the terminal: llama-cli -hf rockypod/neotoi-coder: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 rockypod/neotoi-coder:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf rockypod/neotoi-coder: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 rockypod/neotoi-coder:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf rockypod/neotoi-coder:Q4_K_M
Use Docker
docker model run hf.co/rockypod/neotoi-coder:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use rockypod/neotoi-coder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rockypod/neotoi-coder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rockypod/neotoi-coder", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/rockypod/neotoi-coder:Q4_K_M
- Ollama
How to use rockypod/neotoi-coder with Ollama:
ollama run hf.co/rockypod/neotoi-coder:Q4_K_M
- Unsloth Studio
How to use rockypod/neotoi-coder 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 rockypod/neotoi-coder 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 rockypod/neotoi-coder to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for rockypod/neotoi-coder to start chatting
- Pi
How to use rockypod/neotoi-coder with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf rockypod/neotoi-coder: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": "rockypod/neotoi-coder:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use rockypod/neotoi-coder with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf rockypod/neotoi-coder: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 rockypod/neotoi-coder:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use rockypod/neotoi-coder with Docker Model Runner:
docker model run hf.co/rockypod/neotoi-coder:Q4_K_M
- Lemonade
How to use rockypod/neotoi-coder with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull rockypod/neotoi-coder:Q4_K_M
Run and chat with the model
lemonade run user.neotoi-coder-Q4_K_M
List all available models
lemonade list
Pivot main to family hub: 8B and 4B now in standalone repos rockypod/neotoi-coder-8b and -4b
Browse files
README.md
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language:
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- en
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base_model:
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- Qwen/Qwen3-Coder-14B
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tags:
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- dioxus
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- rust
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- server-functions
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- qwen3
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pipeline_tag: text-generation
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---
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# Neotoi Coder
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A Rust / Dioxus 0.7 specialist LLM. v3.1 ships in **three sizes**
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Fine-Tuning) on Qwen3 base models. Optimized for production-quality
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Dioxus 0.7 components with Tailwind v4 and WCAG 2.2 AAA accessibility.
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| Variant | Base | Params | Q4_K_M | Spec exam (104Q weighted, max 144.5) | Files |
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| **8B** (flagship) | Qwen3-8B | 8.2B (6.95B non-embed) | 4.68 GB | **144.5 / 144.5 β 100.00%** |
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| 4B | Qwen3-4B | 4.0B (3.6B non-embed, tied) | 2.33 GB | 143.5 / 144.5 β 99.31% |
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| 14B (legacy) | Qwen3-Coder-14B | 14.8B (13.2B non-embed) | 8.40 GB | 137.0 / 144.5 β 94.81% |
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All three clear the 90% publication bar **and** the 95% release bar with all per-tier floors PASS. The 8B is the recommended default; pick the 4B if disk / RAM is tight, pick the 14B for the broadest coverage.
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> **
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> dropdown at the top of this page (currently showing `main`) to
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> `v3.1.0-8b` or `v3.1.0-4b` to see and download them.
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## Install via Ollama
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Tier floors (82% on weight-1.0 / 1.5 tiers, 88% on weight-2.0 tiers): all PASS for all three variants.
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The 4B's only miss is Q8 (T1 RSX conversion) β generation truncated mid-`<think>` block. The 14B drops on RSX-heavy questions (Q17, Q22, Q30, Q37, Q39, Q43); v3.2 target.
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## What's new in v3.1 (vs v3.0)
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- **Two new sizes**: 8B and 4B alongside the 14B base, both surpassing the 14B's score.
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| **v3.1 8B** | **Qwen3-8B (8.2B)** | **144.5/144.5 (100.00%)** | **103Q weighted** | **4,880** |
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| v3.1 4B | Qwen3-4B (4.0B, tied) | 143.5/144.5 (99.31%) | 103Q weighted | 4,880 |
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## Files in this
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| File | Format | Size | Use case |
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| `neotoi-coder-v3.1-q4_k_m.gguf` | GGUF Q4_K_M | 8.4 GB | LM Studio, llama.cpp, Ollama (current) |
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| `neotoi-coder-v3-q4_k_m_patched.gguf` | GGUF Q4_K_M | 9 GB | v3.0 legacy |
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| `neotoi-coder-v2.0-q4_k_m.gguf` | GGUF Q4_K_M | 9 GB | v2.0 legacy |
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| `neotoi-coder-v1-q4_k_m_final.gguf` | GGUF Q4_K_M | 9 GB | v1.0 legacy |
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For the 8B and 4B Q4_K_M GGUFs
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## Enabling Thinking Mode
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| Before Assistant | `<\|im_start\|>assistant\n<think>` |
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| After Assistant | `<\|im_end\|>` |
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### Ollama (custom Modelfile)
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```Modelfile
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FROM neotoi-coder-v3.1-q4_k_m.gguf
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SYSTEM You are Neotoi, an expert Rust and Dioxus 0.7 developer.
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```
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Or simply
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```
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ollama pull rockypod/neotoi-coder:15b
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## Transparency
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- **
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- **Exam runner, grader, per-question results:** [GitHub β rockypod/neotoi-coder](https://github.com/rockypod/neotoi-coder)
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- **Ollama:** `ollama pull rockypod/neotoi-coder:8b` (or `:4b`, or `:15b`)
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language:
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- en
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base_model: Qwen/Qwen3-Coder-14B
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tags:
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- dioxus
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- rust
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- server-functions
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- gguf
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- qwen3
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- family-hub
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pipeline_tag: text-generation
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---
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# Neotoi Coder β Family Hub
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A Rust / Dioxus 0.7 specialist LLM. v3.1 ships in **three sizes**, each as
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its own standalone repo:
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| Variant | Repo | Base | Params | Q4_K_M | Spec exam (104Q weighted, max 144.5) |
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| **8B** (flagship) | [`rockypod/neotoi-coder-8b`](https://huggingface.co/rockypod/neotoi-coder-8b) | Qwen3-8B | 8.2B (6.95B non-embed) | 4.68 GB | **144.5 / 144.5 β 100.00%** |
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| 4B | [`rockypod/neotoi-coder-4b`](https://huggingface.co/rockypod/neotoi-coder-4b) | Qwen3-4B | 4.0B (3.6B non-embed, tied) | 2.33 GB | 143.5 / 144.5 β 99.31% |
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| 14B (legacy) | this repo (`rockypod/neotoi-coder`) | Qwen3-Coder-14B | 14.8B (13.2B non-embed) | 8.40 GB | 137.0 / 144.5 β 94.81% |
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All three clear the 90% publication bar **and** the 95% release bar with all per-tier floors PASS. The **8B is the recommended default**; pick the **4B** if disk / RAM is tight (or for ~40% faster generation), pick the **14B** for the broadest coverage of legacy material.
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> Each variant lives in its **own model repo** so it's separately searchable and discoverable on HuggingFace. This page (`rockypod/neotoi-coder`) is the family hub *and* still hosts the legacy 14B GGUFs.
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## Install via Ollama
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Tier floors (82% on weight-1.0 / 1.5 tiers, 88% on weight-2.0 tiers): all PASS for all three variants.
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## What's new in v3.1 (vs v3.0)
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- **Two new sizes**: 8B and 4B alongside the 14B base, both surpassing the 14B's score.
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| **v3.1 8B** | **Qwen3-8B (8.2B)** | **144.5/144.5 (100.00%)** | **103Q weighted** | **4,880** |
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| v3.1 4B | Qwen3-4B (4.0B, tied) | 143.5/144.5 (99.31%) | 103Q weighted | 4,880 |
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## Files in this repo (`rockypod/neotoi-coder`, 14B legacy GGUFs)
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| File | Format | Size | Use case |
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| `neotoi-coder-v3.1-q4_k_m.gguf` | GGUF Q4_K_M | 8.4 GB | LM Studio, llama.cpp, Ollama (current 14B) |
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| `neotoi-coder-v3-q4_k_m_patched.gguf` | GGUF Q4_K_M | 9 GB | v3.0 legacy |
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| `neotoi-coder-v2.0-q4_k_m.gguf` | GGUF Q4_K_M | 9 GB | v2.0 legacy |
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| `neotoi-coder-v1-q4_k_m_final.gguf` | GGUF Q4_K_M | 9 GB | v1.0 legacy |
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For the **8B** and **4B** Q4_K_M GGUFs, go to their dedicated repos:
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- https://huggingface.co/rockypod/neotoi-coder-8b
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- https://huggingface.co/rockypod/neotoi-coder-4b
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## Enabling Thinking Mode
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| Before Assistant | `<\|im_start\|>assistant\n<think>` |
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| After Assistant | `<\|im_end\|>` |
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### Ollama (custom Modelfile, 14B)
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```Modelfile
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FROM neotoi-coder-v3.1-q4_k_m.gguf
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SYSTEM You are Neotoi, an expert Rust and Dioxus 0.7 developer.
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```
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Or simply:
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```
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ollama pull rockypod/neotoi-coder:15b
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## Transparency
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- **Per-variant weights:** [`-8b`](https://huggingface.co/rockypod/neotoi-coder-8b) Β· [`-4b`](https://huggingface.co/rockypod/neotoi-coder-4b) Β· this repo (14B)
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- **Exam runner, grader, per-question results:** [GitHub β rockypod/neotoi-coder](https://github.com/rockypod/neotoi-coder)
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- **Ollama:** `ollama pull rockypod/neotoi-coder:8b` (or `:4b`, or `:15b`)
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