Instructions to use tatjr13/damascus-t2-base-l1 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 tatjr13/damascus-t2-base-l1 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 tatjr13/damascus-t2-base-l1 # Run inference directly in the terminal: llama cli -hf tatjr13/damascus-t2-base-l1
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf tatjr13/damascus-t2-base-l1 # Run inference directly in the terminal: llama cli -hf tatjr13/damascus-t2-base-l1
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 tatjr13/damascus-t2-base-l1 # Run inference directly in the terminal: ./llama-cli -hf tatjr13/damascus-t2-base-l1
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 tatjr13/damascus-t2-base-l1 # Run inference directly in the terminal: ./build/bin/llama-cli -hf tatjr13/damascus-t2-base-l1
Use Docker
docker model run hf.co/tatjr13/damascus-t2-base-l1
- LM Studio
- Jan
- Ollama
How to use tatjr13/damascus-t2-base-l1 with Ollama:
ollama run hf.co/tatjr13/damascus-t2-base-l1
- Unsloth Desktop
- Docker Model Runner
How to use tatjr13/damascus-t2-base-l1 with Docker Model Runner:
docker model run hf.co/tatjr13/damascus-t2-base-l1
- Lemonade
How to use tatjr13/damascus-t2-base-l1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tatjr13/damascus-t2-base-l1
Run and chat with the model
lemonade run user.damascus-t2-base-l1-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
damascus-t2-base-l1
GGUF artifact for DAMASCUS test T2 (test plan v2.1): the untouched tpn-004 base exported with the L1 recipe.
- Source:
Magistral-Small-2509-ultra-uncensored-heretic-v2-BF16.gguf(sha2565d425b36eeff7ce5...), never trained by us. - Export: llama.cpp b10020
llama-quantizewith the evaluator-shaped imatrix โQ4_K_M 32with Q8_0 for attn_q/k/v/output, ffn_down, token embeddings and output tensor (the exact L1 recipe; per-tensor conversion log identical to the L1-im export). - Template variant T1a:
tokenizer.chat_templateset to the T1a variant โ the shipped 305-char Mistral[INST]loop with the "Answer directly and briefly..." system instruction prepended as its own[INST] ... [/INST]block afterbos_token. Template sha256d338a0af9865562ac73b6f67e82fc80a7edd4e86d384a0c0b10caba784f5ae11.
The single file model.gguf is the complete artifact.
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Hardware compatibility
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