Muse-1B is a compact chat language model from Muse Research Lab. It is built for helpful everyday conversation, writing, simple coding help, multilingual assistance, and safe general-purpose responses.

Model Details

Model Developer: Muse Research Lab

Model Architecture: Muse-1B is an auto-regressive, Llama-style decoder-only transformer optimized for compact chat and general assistance.

Model	Params	Input modalities	Output modalities	Context Length	GQA	Shared Embeddings	Knowledge cutoff
Muse-1B	~1B	Multilingual text	Multilingual text and code	8,192 tokens	Yes	Yes	Not specified

Supported Languages: English, German, French, Italian, Spanish, and Portuguese.

Status: This is a compact chat model intended for lightweight assistant-style use.

Capabilities

General chat and question answering
Writing, brainstorming, and rewriting
Simple coding help and explanations
Multilingual responses in English, German, French, Italian, Spanish, and Portuguese
Safe refusal behavior for harmful requests

Quickstart

pip install "transformers>=4.43.0" accelerate torch

python

import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

MODEL_ID = "muse/Muse-1B"

tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(
    MODEL_ID,
    torch_dtype=torch.bfloat16,
    device_map="auto",
)

messages = [
    {"role": "system", "content": "You are Muse-1B, a helpful chat assistant from Muse Research Lab."},
    {"role": "user", "content": "Hi, who are you?"},
]

prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

with torch.inference_mode():
    output_ids = model.generate(
        **inputs,
        max_new_tokens=256,
        temperature=0.7,
        top_p=0.9,
        do_sample=True,
    )

response = tokenizer.decode(output_ids[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True)
print(response)

Intended Use

Muse-1B is intended for lightweight assistant-style use, including chat, drafting, summarization, simple programming support, and multilingual everyday help.

Limitations

May produce incorrect or incomplete answers.
May struggle with advanced reasoning, long coding tasks, or highly specialized domains.
Should not be used as the only source for medical, legal, financial, or safety-critical decisions.
Applications should add their own safeguards when deployed to users.

Safety

Muse-1B is designed to be helpful while refusing clearly harmful requests. For production use, pair the model with application-level safety checks, monitoring, and domain-specific policies.

_{Built by Muse Research Lab}

Muse-research/Muse-1B

Muse-1B