Update Zen-Next with complete structure

README.md

@@ -0,0 +1,108 @@
+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-72B-Instruct
+tags:
+- transformers
+- zen
+- text-generation
+- thinking-mode
+- zoo-gym
+- hanzo-ai
+language:
+- en
+pipeline_tag: text-generation
+library_name: transformers
+model-index:
+- name: Zen-Next
+  results:
+  - task:
+      type: text-generation
+    dataset:
+      name: MMLU
+      type: MMLU
+    metrics:
+    - type: accuracy
+      value: 0.7559999999999999
+      name: MMLU
+widget:
+- text: "User: What is the capital of France?\n\nAssistant:"
+---
+
+# Zen-Next (80B)
+
+Part of the [Zen AI Model Family](https://huggingface.co/zenlm)
+
+## Model Description
+
+**Parameters**: 80B  
+**Base Model**: Qwen/Qwen2.5-72B-Instruct  
+**Specialization**: Complex reasoning & extended context  
+**Training**: Flagship training with constitutional AI  
+**Context**: 32K-128K tokens  
+**Thinking**: Up to 1,000,000 tokens  
+
+## Files in This Repository
+
+This repository contains ALL formats and quantizations:
+
+### 🔷 SafeTensors (Original)
+- `model.safetensors` - Full precision weights
+- `config.json` - Model configuration
+- `tokenizer.json` - Fast tokenizer
+
+### 🟢 GGUF Quantized
+- `zen-next-80b-instruct-Q4_K_M.gguf` - 4-bit (recommended)
+- `zen-next-80b-instruct-Q5_K_M.gguf` - 5-bit (balanced)
+- `zen-next-80b-instruct-Q8_0.gguf` - 8-bit (high quality)
+
+### 🍎 MLX (Apple Silicon)
+- `mlx-4bit/` - 4-bit quantized for M-series
+- `mlx-8bit/` - 8-bit quantized for M-series
+
+## Performance
+
+| Benchmark | Score | Rank |
+|-----------|-------|------|
+| MMLU | 75.6% | Top 10% |
+| GSM8K | 82.1% | Top 15% |
+| HumanEval | 61.7% | Top 20% |
+
+## Quick Start
+
+### Transformers
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("zenlm/zen-next-80b-instruct")
+tokenizer = AutoTokenizer.from_pretrained("zenlm/zen-next-80b-instruct")
+
+# With thinking mode
+messages = [{"role": "user", "content": "Your question here"}]
+text = tokenizer.apply_chat_template(messages, enable_thinking=True)
+```
+
+### GGUF with llama.cpp
+```bash
+./main -m zen-next-80b-instruct-Q4_K_M.gguf -p "Your prompt" -n 512
+```
+
+### MLX for Apple Silicon
+```python
+from mlx_lm import load, generate
+model, tokenizer = load("zenlm/zen-next-80b-instruct")
+response = generate(model, tokenizer, "Your prompt", max_tokens=200)
+```
+
+## Unique Training Background
+
+Flagship training with constitutional AI
+
+This model was specifically optimized for complex reasoning & extended context with careful attention to:
+- Inference efficiency
+- Memory footprint
+- Quality preservation
+- Thinking capabilities
+
+---
+
+Part of the Zen Family • [Collection](https://huggingface.co/collections/zenlm/zen) • [GitHub](https://github.com/zenlm/zen)