106 lines
3.1 KiB
Markdown
106 lines
3.1 KiB
Markdown
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---
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library_name: transformers
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license: apache-2.0
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pipeline_tag: text-generation
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tags:
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- muse
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- chat
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- multilingual
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- text-generation
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language:
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- en
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- de
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- fr
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- it
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- es
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- pt
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---
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# Muse-3B
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Muse-3B is a compact 3B chat language model from **Muse Research Lab**. It is built for helpful everyday conversation, writing, simple coding help, English/German/French assistance, and safe general-purpose responses.
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## Model Details
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**Model Developer:** Muse Research Lab
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**Model Architecture:** Muse-3B is an auto-regressive, Llama-style decoder-only transformer optimized for compact chat and general assistance.
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| Model | Params | Input modalities | Output modalities | Context Length | GQA | Shared Embeddings | Knowledge cutoff |
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| :---- | :---- | :---- | :---- | :---- | :---- | :---- | :---- |
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| Muse-3B | ~3B | Multilingual text | Multilingual text and code | 8,192 tokens | Yes | Yes | Not specified |
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**Supported Languages:** English, German, and French.
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**Status:** This is an early compact chat model intended for lightweight assistant-style use and experimentation.
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## Capabilities
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- General chat and question answering
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- Writing, brainstorming, and rewriting
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- Simple coding help and explanations
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- Multilingual responses in English, German, and French
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- Safe refusal behavior for harmful requests
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## Quickstart
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```bash
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pip install "transformers>=4.43.0" accelerate torch
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```
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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MODEL_ID = "Muse-research/Muse-3B"
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tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
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model = AutoModelForCausalLM.from_pretrained(
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MODEL_ID,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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)
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messages = [
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{"role": "system", "content": "You are Muse-3B, a helpful chat assistant from Muse Research Lab."},
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{"role": "user", "content": "Hi, who are you?"},
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]
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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with torch.inference_mode():
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output_ids = model.generate(
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**inputs,
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max_new_tokens=256,
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temperature=0.7,
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top_p=0.9,
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do_sample=True,
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)
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response = tokenizer.decode(output_ids[0][inputs.input_ids.shape[-1]:], skip_special_tokens=True)
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print(response)
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```
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## Intended Use
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Muse-3B is intended for lightweight assistant-style use, including chat, drafting, summarization, simple programming support, and English/German/French/Italian/Spanish/Portuguese everyday help.
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## Limitations
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- May produce incorrect or incomplete answers.
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- May struggle with advanced reasoning, long coding tasks, or highly specialized domains.
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- Multilingual support is useful but may be less reliable than English.
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- Should not be used as the only source for medical, legal, financial, or safety-critical decisions.
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- Applications should add their own safeguards when deployed to users.
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## Safety
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Muse-3B 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.
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---
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<div align="center">
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<sub>Built by Muse Research Lab</sub>
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</div>
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