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Model: Muse-research/Muse-3B
Source: Original Platform

.gitattributes

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README.md

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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-3B
+
+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.
+
+## Model Details
+
+**Model Developer:** Muse Research Lab
+
+**Model Architecture:** Muse-3B 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-3B | ~3B | Multilingual text | Multilingual text and code | 8,192 tokens | Yes | Yes | Not specified |
+
+**Supported Languages:** English, German, and French.
+
+**Status:** This is an early compact chat model intended for lightweight assistant-style use and experimentation.
+
+## Capabilities
+
+- General chat and question answering
+- Writing, brainstorming, and rewriting
+- Simple coding help and explanations
+- Multilingual responses in English, German, and French
+- 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-research/Muse-3B"
+
+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-3B, 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-3B is intended for lightweight assistant-style use, including chat, drafting, summarization, simple programming support, and English/German/French/Italian/Spanish/Portuguese everyday help.
+
+## Limitations
+
+- May produce incorrect or incomplete answers.
+- May struggle with advanced reasoning, long coding tasks, or highly specialized domains.
+- Multilingual support is useful but may be less reliable than English.
+- 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-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.
+
+---
+
+<div align="center">
+  <sub>Built by Muse Research Lab</sub>
+</div>

chat_template.jinja

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+{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
+You are a helpful AI assistant named SmolLM, trained by Hugging Face<|im_end|>
+' }}{% endif %}{{'<|im_start|>' + message['role'] + '
+' + message['content'] + '<|im_end|>' + '
+'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
+' }}{% endif %}

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "bfloat16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 3072,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 8192,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 24,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "rope_theta": 500000.0,
+    "rope_type": "default"
+  },
+  "tie_word_embeddings": true,
+  "transformers_version": "5.8.0.dev0",
+  "use_cache": true,
+  "vocab_size": 49152
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "pad_token_id": 2,
+  "transformers_version": "5.8.0.dev0",
+  "use_cache": false
+}

model.safetensors

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tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<|im_start|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>"
+  ],
+  "is_local": false,
+  "local_files_only": false,
+  "model_max_length": 8192,
+  "pad_token": "<|im_end|>",
+  "tokenizer_class": "GPT2Tokenizer",
+  "unk_token": "<|endoftext|>",
+  "vocab_size": 49152
+}