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library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- muse
- chat
- multilingual
- text-generation
language:
- en
- de
- fr
- it
- es
- pt
---
# Muse-1B
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
```bash
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.
---
<div align="center">
<sub>Built by Muse Research Lab</sub>
</div> |