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

Libraries

How to use harxsan/model with Transformers:

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

llama-cpp-python

How to use harxsan/model with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="harxsan/model",
	filename="unsloth.Q8_0.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 harxsan/model with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf harxsan/model:Q8_0
# Run inference directly in the terminal:
llama-cli -hf harxsan/model:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf harxsan/model:Q8_0
# Run inference directly in the terminal:
llama-cli -hf harxsan/model:Q8_0

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 harxsan/model:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf harxsan/model:Q8_0

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 harxsan/model:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf harxsan/model:Q8_0

Use Docker

docker model run hf.co/harxsan/model:Q8_0

LM Studio
Jan
Ollama
How to use harxsan/model with Ollama:
```
ollama run hf.co/harxsan/model:Q8_0
```

Unsloth Studio new

How to use harxsan/model 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 harxsan/model 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 harxsan/model to start chatting

Using HuggingFace Spaces for Unsloth

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

Docker Model Runner
How to use harxsan/model with Docker Model Runner:
```
docker model run hf.co/harxsan/model:Q8_0
```

Lemonade

How to use harxsan/model with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull harxsan/model:Q8_0

Run and chat with the model

lemonade run user.model-Q8_0

List all available models

lemonade list

model

File size: 867 Bytes

220dde4

FROM /content/harxsan/model/unsloth.Q8_0.gguf

TEMPLATE """Below are some instructions that describe some tasks. Write responses that appropriately complete each request.{{ if .Prompt }}

### Instruction:
{{ .Prompt }}{{ end }}

### Response:
{{ .Response }}<|im_end|>"""

PARAMETER stop "<|video_pad|>"
PARAMETER stop "<|endoftext|>"
PARAMETER stop "<|quad_start|>"
PARAMETER stop "<|image_pad|>"
PARAMETER stop "<|file_sep|>"
PARAMETER stop "</tool_call>"
PARAMETER stop "<|PAD_TOKEN|>"
PARAMETER stop "<|box_end|>"
PARAMETER stop "<tool_call>"
PARAMETER stop "<|box_start|>"
PARAMETER stop "<|object_ref_start|>"
PARAMETER stop "<|im_start|>"
PARAMETER stop "<|repo_name|>"
PARAMETER stop "<|quad_end|>"
PARAMETER stop "<|object_ref_end|>"
PARAMETER stop "<|im_end|>"
PARAMETER stop "<|vision_"
PARAMETER stop "<|fim_"
PARAMETER temperature 1.5
PARAMETER min_p 0.1