Instructions to use zerolimites/BitNet-TinyDialogues-1.58b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use zerolimites/BitNet-TinyDialogues-1.58b with Transformers:

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

pipe = pipeline("text-generation", model="zerolimites/BitNet-TinyDialogues-1.58b")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("zerolimites/BitNet-TinyDialogues-1.58b")
model = AutoModelForCausalLM.from_pretrained("zerolimites/BitNet-TinyDialogues-1.58b", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use zerolimites/BitNet-TinyDialogues-1.58b 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 zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
# Run inference directly in the terminal:
llama cli -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
# Run inference directly in the terminal:
llama cli -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
# Run inference directly in the terminal:
./build/bin/llama cli -hf zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0

Use Docker

docker model run hf.co/zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0

Llama new
LM Studio
Jan

vLLM

How to use zerolimites/BitNet-TinyDialogues-1.58b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "zerolimites/BitNet-TinyDialogues-1.58b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "zerolimites/BitNet-TinyDialogues-1.58b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0

SGLang

How to use zerolimites/BitNet-TinyDialogues-1.58b 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 "zerolimites/BitNet-TinyDialogues-1.58b" \
    --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": "zerolimites/BitNet-TinyDialogues-1.58b",
		"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 "zerolimites/BitNet-TinyDialogues-1.58b" \
        --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": "zerolimites/BitNet-TinyDialogues-1.58b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use zerolimites/BitNet-TinyDialogues-1.58b with Ollama:
```
ollama run hf.co/zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
```
Unsloth Desktop
Docker Model Runner
How to use zerolimites/BitNet-TinyDialogues-1.58b with Docker Model Runner:
```
docker model run hf.co/zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0
```

Lemonade

How to use zerolimites/BitNet-TinyDialogues-1.58b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull zerolimites/BitNet-TinyDialogues-1.58b:TQ1_0

Run and chat with the model

lemonade run user.BitNet-TinyDialogues-1.58b-TQ1_0

List all available models

lemonade list

Atomic Chat

BitNet-TinyDialogues-1.58b / space /app.py

zerolimites

BitNet b1.58 TinyDialogues: trained checkpoint, GGUF, scripts, patches

655f931 verified 1 day ago

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1.03 kB

#!/usr/bin/env python3
"""Optional Gradio UI for a PRO/paid CPU Space. Static Space uses index.html."""
import os, subprocess, tempfile
import gradio as gr
from huggingface_hub import hf_hub_download

MODEL_REPO = os.environ.get('MODEL_REPO', 'zerolimites/BitNet-TinyDialogues-1.58b')
GGUF_FILE = os.environ.get('GGUF_FILE', 'gguf/bitnet-tinydialogues-TQ1_0.gguf')
LLAMA_CLI = os.environ.get('LLAMA_CLI', 'llama-cli')

def load_model():
    return hf_hub_download(MODEL_REPO, GGUF_FILE)

def chat(message, history):
    model = load_model()
    prompt = 'User: ' + message + ' Assistant:'
    cmd = [LLAMA_CLI, '-m', model, '-p', prompt, '-n', '64', '-c', '128',
           '--temp', '0.8', '-t', '2', '-r', 'User:', '--no-display-prompt', '--simple-io']
    out = subprocess.run(cmd, capture_output=True, text=True, timeout=120)
    return out.stdout.strip() or out.stderr.strip()

demo = gr.ChatInterface(fn=chat, title='BitNet TinyDialogues CPU')
if __name__ == '__main__':
    demo.launch(server_name='0.0.0.0', server_port=7860)

	#!/usr/bin/env python3
	"""Optional Gradio UI for a PRO/paid CPU Space. Static Space uses index.html."""
	import os, subprocess, tempfile
	import gradio as gr
	from huggingface_hub import hf_hub_download

	MODEL_REPO = os.environ.get('MODEL_REPO', 'zerolimites/BitNet-TinyDialogues-1.58b')
	GGUF_FILE = os.environ.get('GGUF_FILE', 'gguf/bitnet-tinydialogues-TQ1_0.gguf')
	LLAMA_CLI = os.environ.get('LLAMA_CLI', 'llama-cli')

	def load_model():
	return hf_hub_download(MODEL_REPO, GGUF_FILE)

	def chat(message, history):
	model = load_model()
	prompt = 'User: ' + message + ' Assistant:'
	cmd = [LLAMA_CLI, '-m', model, '-p', prompt, '-n', '64', '-c', '128',
	'--temp', '0.8', '-t', '2', '-r', 'User:', '--no-display-prompt', '--simple-io']
	out = subprocess.run(cmd, capture_output=True, text=True, timeout=120)
	return out.stdout.strip() or out.stderr.strip()

	demo = gr.ChatInterface(fn=chat, title='BitNet TinyDialogues CPU')
	if __name__ == '__main__':
	demo.launch(server_name='0.0.0.0', server_port=7860)