初始化项目，由ModelHub XC社区提供模型

Model: razy101/emojify-300m
Source: Original Platform

README.md

@@ -0,0 +1,48 @@
+---
+base_model: unsloth/gemma-3-270m-it
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- gemma3_text
+license: apache-2.0
+language:
+- en
+---
+
+---
+license: apache-2.0
+base_model: google/gemma-3-270m-it
+library_name: transformers
+tags:
+- unsloth
+- gemma-3
+- emoji
+- translation
+- multilingual
+- gguf
+- edge-ai
+datasets:
+- custom-curated-emoji-distillation
+---
+
+# 🚀 Emojify-300M (Gemma-3-270M Fine-tuned)
+
+**Emojify-300M** is a hyper-compact, specialized Large Language Model (LLM) designed for **semantic text-to-emoji distillation**. Based on the **Gemma-3-270M-IT** architecture, this model is optimized for edge computing and ultra-low latency applications.
+
+## 🛠 Technical Specifications
+- **Architecture:** Gemma-3 (270M parameters)
+- **Fine-tuning Method:** LoRA (Low-Rank Adaptation) via **Unsloth**
+- **Context Window:** 2048 tokens
+- **Language Support:** Native Multilingual
+
+## 📈 Performance & Benchmarks (Local CPU)
+Tested on consumer-grade hardware (e.g., laptop CPU):
+- **Prompt Evaluation:** ~210 tokens/s
+- **Token Generation (Eval):** ~48 tokens/s
+- **Total Latency:** < 500ms (near-instant response)
+
+## 🎯 Key Features
+- **Zero-Shot Cross-Lingual Transfer:** Leveraging Gemma 3's robust base weights, the model accurately processes languages not explicitly present in the fine-tuning set.
+- **Noise Suppression:** Specifically trained to inhibit conversational filler and "hallucinated" text, focusing strictly on relevant emoji output.
+- **EOS Stability:** Fine-tuned to respect End-of-Sequence (EOS) tokens, preventing the common "looping" behavior seen in smaller models.