Instructions to use Masterjp123/Mimicra-V1-13B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Masterjp123/Mimicra-V1-13B-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Masterjp123/Mimicra-V1-13B-GGUF")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Masterjp123/Mimicra-V1-13B-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Masterjp123/Mimicra-V1-13B-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 Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S # Run inference directly in the terminal: llama cli -hf Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S # Run inference directly in the terminal: llama cli -hf Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
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 Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
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 Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
Use Docker
docker model run hf.co/Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
- LM Studio
- Jan
- vLLM
How to use Masterjp123/Mimicra-V1-13B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Masterjp123/Mimicra-V1-13B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Masterjp123/Mimicra-V1-13B-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
- SGLang
How to use Masterjp123/Mimicra-V1-13B-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Masterjp123/Mimicra-V1-13B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Masterjp123/Mimicra-V1-13B-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Masterjp123/Mimicra-V1-13B-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Masterjp123/Mimicra-V1-13B-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use Masterjp123/Mimicra-V1-13B-GGUF with Ollama:
ollama run hf.co/Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
- Unsloth Studio
How to use Masterjp123/Mimicra-V1-13B-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 Masterjp123/Mimicra-V1-13B-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 Masterjp123/Mimicra-V1-13B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Masterjp123/Mimicra-V1-13B-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Masterjp123/Mimicra-V1-13B-GGUF with Docker Model Runner:
docker model run hf.co/Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
- Lemonade
How to use Masterjp123/Mimicra-V1-13B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Masterjp123/Mimicra-V1-13B-GGUF:Q4_K_S
Run and chat with the model
lemonade run user.Mimicra-V1-13B-GGUF-Q4_K_S
List all available models
lemonade list
Commit ·
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Parent(s): 6ee020f
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README.md
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## Perpose of this Model:
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This Model was selectivly Merged with Models I have made through Merging, Models with high rankings And Models I liked using to make a ultimatly great model;
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Which is Good at RP, uncensored, Smart and creative
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Currently no Gptq and AWQ.
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## Model Parts:
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> [Magdump-13b](https://huggingface.co/boomerchan/Magdump-13b) RP Model
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## Perpose of this Model:
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This Model was selectivly Merged with Models I have made through Merging, Models with high rankings And Models I liked using to make a ultimatly great model;
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Which is Good at RP, uncensored, Smart and creative.
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This is a GGUF version of Mimicra
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## FP16 weights or other Quants
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[FP16](https://huggingface.co/Masterjp123/Mimicra-V1-13B)
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No other quants currently
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## Model Parts:
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> [Magdump-13b](https://huggingface.co/boomerchan/Magdump-13b) RP Model
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