Instructions to use nesymerp1/Nesys_engine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nesymerp1/Nesys_engine with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("nesymerp1/Nesys_engine", dtype="auto")

llama-cpp-python

How to use nesymerp1/Nesys_engine with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="nesymerp1/Nesys_engine",
	filename="BrokenDan_Q4_K_S.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 nesymerp1/Nesys_engine 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 nesymerp1/Nesys_engine:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf nesymerp1/Nesys_engine:Q4_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf nesymerp1/Nesys_engine:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf nesymerp1/Nesys_engine: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 nesymerp1/Nesys_engine:Q4_K_S
# Run inference directly in the terminal:
./llama-cli -hf nesymerp1/Nesys_engine: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 nesymerp1/Nesys_engine:Q4_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf nesymerp1/Nesys_engine:Q4_K_S

Use Docker

docker model run hf.co/nesymerp1/Nesys_engine:Q4_K_S

LM Studio
Jan
Ollama
How to use nesymerp1/Nesys_engine with Ollama:
```
ollama run hf.co/nesymerp1/Nesys_engine:Q4_K_S
```

Unsloth Studio

How to use nesymerp1/Nesys_engine 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 nesymerp1/Nesys_engine 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 nesymerp1/Nesys_engine to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for nesymerp1/Nesys_engine to start chatting

Atomic Chat new
Docker Model Runner
How to use nesymerp1/Nesys_engine with Docker Model Runner:
```
docker model run hf.co/nesymerp1/Nesys_engine:Q4_K_S
```

Lemonade

How to use nesymerp1/Nesys_engine with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull nesymerp1/Nesys_engine:Q4_K_S

Run and chat with the model

lemonade run user.Nesys_engine-Q4_K_S

List all available models

lemonade list

Nesys_engine / README.md

???

Update README.md

5d97562 verified 5 months ago

preview code

Raw

History Blame Contribute Delete

2.37 kB

	---
	base_model:
	- Delta-Vector/Austral-24B-Winton
	- Delta-Vector/MS3.2-Austral-24B-KTO
	- ReadyArt/The-Omega-Directive-M-24B-v1.1
	- PocketDoc/Dans-PersonalityEngine-V1.3.0-24b
	library_name: transformers
	tags:
	- mergekit
	- merge

	---
	# Merge overview

	This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). There are no higher quants available for this model, only one due to hardware limitations.

	## Merge Details
	### Merge Method

	This model was merged using the [DARE TIES](https://arxiv.org/abs/2311.03099) merge method using [PocketDoc/Dans-PersonalityEngine-V1.3.0-24b](https://huggingface.co/PocketDoc/Dans-PersonalityEngine-V1.3.0-24b) as a base.
	The intention of this merge is to essensially make a model that is capable of roleplaying in NSFW,SFW settings all in one, with smarts involved. Moreover overlap multiple unique writing styles.





	### Models Merged

	The following models were included in the merge:
	* [Delta-Vector/Austral-24B-Winton](https://huggingface.co/Delta-Vector/Austral-24B-Winton)
	* [ReadyArt/The-Omega-Directive-M-24B-v1.1](ReadyArt/The-Omega-Directive-M-24B-v1.1)
	* [PocketDoc/Dans-PersonalityEngine-V1.3.0-24b](https://huggingface.co/PocketDoc/Dans-PersonalityEngine-V1.3.0-24b)
	* [Delta-Vector/MS3.2-Austral-24B-KTO](https://huggingface.co/Delta-Vector/MS3.2-Austral-Winton)

	### Configuration

	The following YAML configuration was used to produce this model:

	```yaml
	models:
	- model: Delta-Vector/MS3.2-Austral-24B-KTO
	parameters:
	weight: 0.3
	density: 0.3
	- model: Delta-Vector/Austral-24B-Winton
	parameters:
	weight: 0.3
	density: 0.5
	- model: ReadyArt/The-Omega-Directive-M-24B-v1.1
	parameters:
	weight: 0.2
	density: 0.3
	merge_method: ties
	base_model: PocketDoc/Dans-PersonalityEngine-V1.3.0-24b
	dtype: bfloat16
	outtype: bfloat16
	```

	### Usage guide

	The prompting format is refered to as Dan's chat for this model.

	```yaml
	<\|system\|>system prompt<\|endoftext\|><\|user\|>Hi there!<\|endoftext\|><\|assistant\|>Hey, how can I help?<\|endoftext\|>
	```


	I would advise starting with adaptive.p at the settings:
	target: 0,55
	decay: 0.9
	min_p: 0.04

	You are free to experiment to set samplers to your liking, this model is under testing phase and users are free to experiment with samplers. The only main requirement is Prompt guide.