Instructions to use QuantFactory/MN-12B-Lyra-v4a1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use QuantFactory/MN-12B-Lyra-v4a1-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="QuantFactory/MN-12B-Lyra-v4a1-GGUF", filename="MN-12B-Lyra-v4a1.Q2_K.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use QuantFactory/MN-12B-Lyra-v4a1-GGUF 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 QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf QuantFactory/MN-12B-Lyra-v4a1-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 QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf QuantFactory/MN-12B-Lyra-v4a1-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 QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M
Use Docker
docker model run hf.co/QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use QuantFactory/MN-12B-Lyra-v4a1-GGUF with Ollama:
ollama run hf.co/QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M
- Unsloth Studio
How to use QuantFactory/MN-12B-Lyra-v4a1-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 QuantFactory/MN-12B-Lyra-v4a1-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 QuantFactory/MN-12B-Lyra-v4a1-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for QuantFactory/MN-12B-Lyra-v4a1-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use QuantFactory/MN-12B-Lyra-v4a1-GGUF with Docker Model Runner:
docker model run hf.co/QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M
- Lemonade
How to use QuantFactory/MN-12B-Lyra-v4a1-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull QuantFactory/MN-12B-Lyra-v4a1-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MN-12B-Lyra-v4a1-GGUF-Q4_K_M
List all available models
lemonade list
llm.create_chat_completion(
messages = "No input example has been defined for this model task."
)QuantFactory/MN-12B-Lyra-v4a1-GGUF
This is quantized version of Sao10K/MN-12B-Lyra-v4a1 created using llama.cpp
Original Model Card
Mistral-NeMo-12B-Lyra-v4, layered over Lyra-v3, which was built on top of Lyra-v2a2, which itself was built upon Lyra-v2a1.
Model Versioning
Lyra-v1 [Merge of Custom Roleplay & Instruct Trains, on Different Formats]
|
| [Additional SFT on 10% of Previous Data, Mixed]
v
Lyra-v2a1
|
| [Low Rank SFT Step + Tokenizer Diddling]
v
Lyra-v2a2
|
| [RL Step Performed on Multiturn Sets, Magpie-style Responses by Lyra-v2a2 for Rejected Data]
v
Lyra-v3
|
| [Backmerge to v2a1 + LoRA Extraction + Low Rank SFT Step for Coherency]
v
Lyra-v4
This uses ChatML, or any of its variants which were included in previous versions.
<|im_start|>system
This is the system prompt.<|im_end|>
<|im_start|>user
Instructions placed here.<|im_end|>
<|im_start|>assistant
The model's response will be here.<|im_end|>
--------------------------------------------------
[INST]system
This is another system prompt.[/INST]
[INST]user
Your instructions placed here.[/INST]
[INST]assistant
The model's response will be here.[/INST]
Recommended Samplers:
Temperature: 0.6 - 1 # I recommend lowering it a litte for v4?
min_p: 0.1 - 0.2 # Crucial for NeMo
Recommended Stopping Strings:
<|im_end|>
</s>
[/INST]
Introduces run-off generations at times, as seen in v2a2. It's layered on top of older models, so eh, makes sense. Easy to cut out though.
Notes
- Some people have been having issues with run-on generations for Lyra-v3. Kind of weird, when I never had issues.
- Anyway, make sure not to skip special tokens, or ban EOS tokens. I think this is the main problem that happens when v3 was to be quanted. The special tokens map config is fucked in v3, Quantizing tools likely spazzed out seeing it. I blame llamafactory for it. It ran fine unquantised.
- I like long generations, though I can control it easily to create short ones. If you're struggling, prompt better. Fix your system prompts, use an Author's Note, use a prefill. They are there for a reason.
- Lyra passes my internal benchmark suite, hence why I'm releasing it. Do I like it? Yes? it's out. that's it. They are my models for my personal enjoyment first.
- Issues like roleplay format are what I consider worthless, as it follows few-shot examples fine. This is not a priority for me to 'fix', as I see no isses with it. Same with excessive generations. Its easy to cut out.
- If you don't like it, just try another model? Plenty of other choices. Ymmv, I like it.
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# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="QuantFactory/MN-12B-Lyra-v4a1-GGUF", filename="", )