初始化项目，由ModelHub XC社区提供模型

Model: aaravriyer193/MonkeGpt-Vivace
Source: Original Platform

README.md

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+---
+library_name: transformers
+inference: true
+pipeline_tag: text-generation
+---
+# 🐵 MonkeGpt-Vivace 🎶
+
+## 🎹 Overview
+
+**MonkeGpt-Vivace** is a high-speed, instruction-tuned language model based on the **Qwen2.5-0.5B** architecture. It has been fine-tuned using the **UltraChat 200k** dataset to transform it from a base autocomplete engine into a snappy, conversational assistant.
+
+The name **"Vivace"** reflects its performance: lightweight, lively, and incredibly fast. At 0.5 billion parameters, it is optimized for edge deployment and serverless CPU inference.
+
+---
+
+## 🍌 Features
+
+* **Instruction Following:** Unlike the base model, Vivace understands user/assistant roles.
+* **Lightweight Brain:** Fits into ~1.1GB of VRAM or System RAM.
+* **High Tempo:** Designed for low-latency responses (30-50 tokens/sec on modern CPUs).
+* **Clean Dialogue:** Fine-tuned to avoid the "hallucination loops" common in small base models.
+
+---
+
+## 🎼 Training Details
+
+* **Base Model:** `Qwen/Qwen2.5-0.5B`
+* **Dataset:** `HuggingFaceH4/ultrachat_200k` (SFT subset)
+* **Hardware:** 1x NVIDIA H100 (Lightning AI)
+* **Epochs:** 2 (Optimized for balance and credit conservation)
+* **Precision:** `BFloat16`
+* **Optimizer:** `AdamW (Fused)`
+
+---
+
+## 🎸 Quick Start (Inference)
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "aaravriyer193/MonkeGpt-Vivace"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto")
+
+prompt = "Explain why monkeys like music in three short sentences."
+messages = [{"role": "user", "content": prompt}]
+
+inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to("cuda")
+outputs = model.generate(inputs, max_new_tokens=100)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+
+```
+
+---
+
+## 🥁 Limitations
+
+While MonkeGpt-Vivace is smart for its size, it is still a 0.5B parameter model. It may struggle with complex mathematical proofs, deep philosophical reasoning, or very long-term memory across thousands of tokens.
+
+---
+
+## 🐒 About the Creator
+
+Developed by **aaravriyer193** during a high-intensity 4-hour sprint on Lightning AI. 🚀