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

Libraries

How to use kygbjs/primus_exploit_finetune with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="kygbjs/primus_exploit_finetune",
	filename="unsloth.BF16.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use kygbjs/primus_exploit_finetune with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf kygbjs/primus_exploit_finetune:BF16
# Run inference directly in the terminal:
llama-cli -hf kygbjs/primus_exploit_finetune:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf kygbjs/primus_exploit_finetune:BF16
# Run inference directly in the terminal:
llama-cli -hf kygbjs/primus_exploit_finetune:BF16

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 kygbjs/primus_exploit_finetune:BF16
# Run inference directly in the terminal:
./llama-cli -hf kygbjs/primus_exploit_finetune:BF16

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 kygbjs/primus_exploit_finetune:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf kygbjs/primus_exploit_finetune:BF16

Use Docker

docker model run hf.co/kygbjs/primus_exploit_finetune:BF16

LM Studio
Jan
Ollama
How to use kygbjs/primus_exploit_finetune with Ollama:
```
ollama run hf.co/kygbjs/primus_exploit_finetune:BF16
```

Unsloth Studio new

How to use kygbjs/primus_exploit_finetune 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 kygbjs/primus_exploit_finetune 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 kygbjs/primus_exploit_finetune to start chatting

Using HuggingFace Spaces for Unsloth

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

Docker Model Runner
How to use kygbjs/primus_exploit_finetune with Docker Model Runner:
```
docker model run hf.co/kygbjs/primus_exploit_finetune:BF16
```

Lemonade

How to use kygbjs/primus_exploit_finetune with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull kygbjs/primus_exploit_finetune:BF16

Run and chat with the model

lemonade run user.primus_exploit_finetune-BF16

List all available models

lemonade list

primus_exploit_finetune

File size: 503 Bytes

63e2d4f


FROM C:\Users\zrt\Desktop\kygbjs\primus_exploit_finetune\unsloth.F16.gguf
TEMPLATE """{{ if .System }}<|start_header_id|>system<|end_header_id|>

{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>

{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>

{{ .Response }}<|eot_id|>"""
PARAMETER stop "<|start_header_id|>"
PARAMETER stop "<|end_header_id|>"
PARAMETER stop "<|eot_id|>"
PARAMETER temperature 1.5
PARAMETER min_p 0.1