Instructions to use N-Bot-Int/ZoraBetaA2-Q16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use N-Bot-Int/ZoraBetaA2-Q16 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="N-Bot-Int/ZoraBetaA2-Q16")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("N-Bot-Int/ZoraBetaA2-Q16", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use N-Bot-Int/ZoraBetaA2-Q16 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 N-Bot-Int/ZoraBetaA2-Q16:F16
# Run inference directly in the terminal:
llama cli -hf N-Bot-Int/ZoraBetaA2-Q16:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf N-Bot-Int/ZoraBetaA2-Q16:F16
# Run inference directly in the terminal:
llama cli -hf N-Bot-Int/ZoraBetaA2-Q16:F16

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 N-Bot-Int/ZoraBetaA2-Q16:F16
# Run inference directly in the terminal:
./llama-cli -hf N-Bot-Int/ZoraBetaA2-Q16:F16

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 N-Bot-Int/ZoraBetaA2-Q16:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf N-Bot-Int/ZoraBetaA2-Q16:F16

Use Docker

docker model run hf.co/N-Bot-Int/ZoraBetaA2-Q16:F16

LM Studio
Jan

vLLM

How to use N-Bot-Int/ZoraBetaA2-Q16 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "N-Bot-Int/ZoraBetaA2-Q16"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "N-Bot-Int/ZoraBetaA2-Q16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/N-Bot-Int/ZoraBetaA2-Q16:F16

SGLang

How to use N-Bot-Int/ZoraBetaA2-Q16 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "N-Bot-Int/ZoraBetaA2-Q16" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "N-Bot-Int/ZoraBetaA2-Q16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "N-Bot-Int/ZoraBetaA2-Q16" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "N-Bot-Int/ZoraBetaA2-Q16",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use N-Bot-Int/ZoraBetaA2-Q16 with Ollama:
```
ollama run hf.co/N-Bot-Int/ZoraBetaA2-Q16:F16
```

Unsloth Studio

How to use N-Bot-Int/ZoraBetaA2-Q16 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 N-Bot-Int/ZoraBetaA2-Q16 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 N-Bot-Int/ZoraBetaA2-Q16 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for N-Bot-Int/ZoraBetaA2-Q16 to start chatting

Docker Model Runner
How to use N-Bot-Int/ZoraBetaA2-Q16 with Docker Model Runner:
```
docker model run hf.co/N-Bot-Int/ZoraBetaA2-Q16:F16
```

Lemonade

How to use N-Bot-Int/ZoraBetaA2-Q16 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull N-Bot-Int/ZoraBetaA2-Q16:F16

Run and chat with the model

lemonade run user.ZoraBetaA2-Q16-F16

List all available models

lemonade list

Atomic Chat

ItsMeDevRoland commited on Jun 21, 2025

Commit

ead1843

verified ·

1 Parent(s): 18d8e61

Update README.md

Browse files

Files changed (1) hide show

README.md +39 -6

README.md CHANGED Viewed

@@ -11,12 +11,45 @@ language:
 - en
 ---
-# Uploaded  model
-- **Developed by:** N-Bot-Int
-- **License:** apache-2.0
-- **Finetuned from model :** HuggingFaceH4/zephyr-7b-beta
-This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)

 - en
 ---
+---
+license: apache-2.0
+datasets:
+- openerotica/mixed-rp
+- kingbri/PIPPA-shareGPT
+- flammenai/character-roleplay-DPO
+language:
+- en
+base_model:
+- N-Bot-Int/OpenElla3-Llama3.2B
+pipeline_tag: text-generation
+tags:
+- unsloth
+- Uncensored
+- text-generation-inference
+- transformers
+- unsloth
+- llama
+- trl
+- roleplay
+- conversational
+---
+# Support Us Through
+  - [![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/J3J61D8NHV)
+  - [https://ko-fi.com/nexusnetworkint](Official Ko-FI link!)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/sm_V28yhG4zhzoeuI42-e.png)
+# GGUF Version
+  **GGUF** with Quants! Allowing you to run models using KoboldCPP and other AI Environments!
+# Quantizations:
+| Quant Type    | Benefits                                          | Cons                                              |
+|---------------|---------------------------------------------------|---------------------------------------------------|
+| **Q16_0**     | ✅ Highest accuracy (closest to full model)       | ❌ Requires significantly more VRAM/RAM          |
+|               | ✅ Best for complex reasoning & detailed outputs  | ❌ Slower inference compared to Q4 & Q5          |
+|               | ✅ Suitable for high-end GPUs & serious workloads | ❌ Larger file size (takes more storage)         |
+# Model Details:
+  Read the Model details on huggingface
+  [Model Detail Here](https://huggingface.co/N-Bot-Int/ZoraBetaA2)