Instructions to use FPHam/PlotBot-V2-13b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

Buy Plot-Bot Ko-fi

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.

Downloads last month: 9

GGUF

Model size

13B params

Architecture

llama

Hardware compatibility

4-bit

5-bit

Inference Providers NEW

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