Text Generation
Safetensors
GGUF
English
nae1
neuralai
causal-lm
llama-cpp
from-scratch
pretraining
sft
tool-use
local-ai
tiny-model
conversational
Instructions to use Subject-Emu-5259/NeuralAI-Nae1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Subject-Emu-5259/NeuralAI-Nae1 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M # Run inference directly in the terminal: llama cli -hf Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M # Run inference directly in the terminal: llama cli -hf Subject-Emu-5259/NeuralAI-Nae1: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 Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Subject-Emu-5259/NeuralAI-Nae1: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 Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M
Use Docker
docker model run hf.co/Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Subject-Emu-5259/NeuralAI-Nae1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Subject-Emu-5259/NeuralAI-Nae1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Subject-Emu-5259/NeuralAI-Nae1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M
- Ollama
How to use Subject-Emu-5259/NeuralAI-Nae1 with Ollama:
ollama run hf.co/Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Subject-Emu-5259/NeuralAI-Nae1 with Docker Model Runner:
docker model run hf.co/Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M
- Lemonade
How to use Subject-Emu-5259/NeuralAI-Nae1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Subject-Emu-5259/NeuralAI-Nae1:Q4_K_M
Run and chat with the model
lemonade run user.NeuralAI-Nae1-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Commit History
Today
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Model card: SFT v12.2 LoRA assistant release (step-12000) — content update, design unchanged
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Yesterday
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Card: SFT v11 is the current release (golden-40 35.5/40, PPL 48.08, multiturn12 11/12)
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Card: v10 release now at repo root; v1-era GGUF ports removed (they misreported model size)
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Model card: SFT v10 LoRA assistant release (step-12000) — content update, design unchanged
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Add Links section: live chat demo, company site, GitHub repos
Verified signatureCross-links the model card with the live NEA1 chat site, the NeuralAI company site, and the GitHub repos. Mirrors the GitHub README/MODEL_CARD change.d20d6c1 -
Model card: SFT v9 LoRA assistant release (step-12000) — content update, design unchanged
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2 days ago
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Model card: production serving moved to SFT v8 (Render, 2026-10-21)
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Model card: SFT v8 assistant release (step-16000) — content update, design unchanged
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10 days ago
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Refresh card to step-80000 2000-doc eval; add Q4 GGUF, v3 charts, and eval reports
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11 days ago
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15 days ago
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step-32000 refresh: PPL 54.16 (corrected-label cycle), weights/eval/charts/badges + fresh-corpus cross-check
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step-28000 refresh: PPL 146.17, weights/eval/charts/badges
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Refresh to step-24000: weights (Q4/f32), eval report, README, showcase assets (PPL 147.97)
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Refresh showcase to step-20000: PPL 148.84, eval_step20000 report, banner + comparison assets
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16 days ago
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Publish Nae1 step-8000: card, graphics, GGUFs (f32 + Q4_K_M), config, tokenizer, eval report
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