Instructions to use microsoft/bitnet-b1.58-2B-4T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/bitnet-b1.58-2B-4T with Transformers:

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

pipe = pipeline("text-generation", model="microsoft/bitnet-b1.58-2B-4T", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("microsoft/bitnet-b1.58-2B-4T", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("microsoft/bitnet-b1.58-2B-4T", trust_remote_code=True)
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use microsoft/bitnet-b1.58-2B-4T with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "microsoft/bitnet-b1.58-2B-4T"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "microsoft/bitnet-b1.58-2B-4T",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/microsoft/bitnet-b1.58-2B-4T

SGLang

How to use microsoft/bitnet-b1.58-2B-4T 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 "microsoft/bitnet-b1.58-2B-4T" \
    --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": "microsoft/bitnet-b1.58-2B-4T",
		"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 "microsoft/bitnet-b1.58-2B-4T" \
        --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": "microsoft/bitnet-b1.58-2B-4T",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use microsoft/bitnet-b1.58-2B-4T with Docker Model Runner:
```
docker model run hf.co/microsoft/bitnet-b1.58-2B-4T
```

Ollama support

by BB8-dev - opened Apr 17, 2025

Discussion

BB8-dev

Apr 17, 2025

‌‌‌When can you support OLLAMA? It's very friendly for low-end hardware.

NItroAMD

Apr 17, 2025

Ollama supports gguf's, but it fails:
https://huggingface.co/docs/hub/ollama

ollama run hf.co/microsoft/bitnet-b1.58-2B-4T-gguf
pulling manifest
pulling 13939ce50303... 100% ▕████████████████████████████████████████████████████████▏ 1.8 GB
pulling d3e74eb82b03... 100% ▕████████████████████████████████████████████████████████▏ 46 B
pulling 33628a28ae3a... 100% ▕████████████████████████████████████████████████████████▏ 19 B
pulling abe99eb73b8f... 100% ▕████████████████████████████████████████████████████████▏ 201 B
verifying sha256 digest
writing manifest
success
Error: unable to load model: C:\Users\xxxxx.ollama\models\blobs\sha256-13939ce5030319a35db346e5dba7a3a3bd599dfc18b113a2a97446ff964714c5

betmig

Apr 22, 2025

I'm also getting issues:

docker exec ollama ollama run hf.co/microsoft/bitnet-b1.58-2B-4T-gguf
pulling manifest
pulling 13939ce50303... 100% ▕████████████████▏ 1.8 GB
pulling d3e74eb82b03... 100% ▕████████████████▏ 46 B
pulling 33628a28ae3a... 100% ▕████████████████▏ 19 B
pulling abe99eb73b8f... 100% ▕████████████████▏ 201 B
verifying sha256 digest
writing manifest
success
Error: llama runner process has terminated: GGML_ASSERT(0 <= info->type && info->type < GGML_TYPE_COUNT) failed