Instructions to use FPHam/PlotBot-V2-13b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use FPHam/PlotBot-V2-13b-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="FPHam/PlotBot-V2-13b-GGUF", filename="PlotBot-V2-13b_Q4_K_M.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use FPHam/PlotBot-V2-13b-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf FPHam/PlotBot-V2-13b-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf FPHam/PlotBot-V2-13b-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf FPHam/PlotBot-V2-13b-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf FPHam/PlotBot-V2-13b-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 FPHam/PlotBot-V2-13b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf FPHam/PlotBot-V2-13b-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 FPHam/PlotBot-V2-13b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf FPHam/PlotBot-V2-13b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/FPHam/PlotBot-V2-13b-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use FPHam/PlotBot-V2-13b-GGUF with Ollama:
ollama run hf.co/FPHam/PlotBot-V2-13b-GGUF:Q4_K_M
- Unsloth Studio new
How to use FPHam/PlotBot-V2-13b-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 FPHam/PlotBot-V2-13b-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 FPHam/PlotBot-V2-13b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for FPHam/PlotBot-V2-13b-GGUF to start chatting
- Docker Model Runner
How to use FPHam/PlotBot-V2-13b-GGUF with Docker Model Runner:
docker model run hf.co/FPHam/PlotBot-V2-13b-GGUF:Q4_K_M
- Lemonade
How to use FPHam/PlotBot-V2-13b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull FPHam/PlotBot-V2-13b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.PlotBot-V2-13b-GGUF-Q4_K_M
List all available models
lemonade list
PlotBOT 13b LLama 2 model for writing story plots (Version 2 - strictly plots) - Uncensored
Version 2 is focused on writing plots and not gasslighting users with "funny" opiniated chitchat like the short-lived Version 1. I know it was adorable at first, but everything would ultimately result in sounding the same. That's a bad novelty act.
The experimental V1 was too overtrained on a single style with little variation and it would just repeat the same language cliches and word collocations to the point of becoming one trick pony. (Now that's collocation cliche!)
A separate "unhinged" model (for fun) may be released later where I may go the other way, with deeper dataset.
For now I'll stay away from mixing function and style.
PlotBOT V2 uses ALPACA instruct
Below is an instruction that describes a task. Write a response that appropriately completes the request.
### Instruction:
Write me a plot for sci-fi detective story. The main character name is Elisabeth Windex. She is lonely PI working on the Moon.
### Response:
Training
This is mostly an experiment to test my DEMENTOR plain text learning. DEMENTOR stands for Deep Memorization Enforcement Through Overlapping and Repetition, and I spent good 10 minutes with ChatGPT to come up with that acronym, so shush.
It is geared towards sci-fi and fantasy but can extrapolate any style.
Plagiarism warning
Being LLM and LLama, the model can borrow subplots and tropes from exisitng works and can also associate names that exists in literature. That's nothing new of course, I'm just reminding you when you meet John Snow on some frozen plannet and he really wants to fly dragon.
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