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--- |
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base_model: openai/gpt-oss-20b |
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base_model_relation: merge |
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library_name: transformers |
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pipeline_tag: text-generation |
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tags: |
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- sft |
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- transformers |
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- trl |
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license: apache-2.0 |
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language: |
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- en |
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- ko |
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--- |
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# Vayne-V1 |
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**Vayne-V1** is a **compact, efficient, and high-performance enterprise LLM** optimized for **AI agent frameworks**, **MCP-based tool orchestration**, **Retrieval-Augmented Generation (RAG) pipelines**, and **secure on-premise deployment**. |
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- ✅ Lightweight architecture for fast inference and low resource usage |
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- ⚙️ Seamless integration with modern AI agent frameworks |
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- 🔗 Built-in compatibility for MCP-based multi-tool orchestration |
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- 🔍 Optimized for enterprise-grade RAG systems |
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- 🛡️ Secure deployment in private or regulated environments |
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--- |
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## Key Design Principles |
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| Feature | Description | |
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|----------|-------------| |
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| 🔐 Private AI Ready | Deploy fully **on-premise** or in **air-gapped** secure environments | |
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| ⚡ Lightweight Inference | **Single-GPU optimized** architecture for fast and cost-efficient deployment | |
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| 🧠 Enterprise Reasoning | Structured output and instruction-following for **business automation** | |
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| 🔧 Agent & MCP Native | Built for **AI agent frameworks** and **MCP-based tool orchestration** | |
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| 🔍 RAG Enhanced | Optimized for **retrieval workflows** with vector DBs (FAISS, Milvus, pgvector, etc.) | |
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--- |
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## Model Architecture & Training |
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| Specification | Details | |
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|---------------|---------| |
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| 🧬 Base Model | GPT-OSS-20B | |
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| 🔢 Parameters | ~20B | |
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| 🎯 Precision | FP16 / BF16 | |
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| 🧱 Architecture | Decoder-only Transformer | |
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| 📏 Context Length | 4K tokens | |
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| ⚡ Inference | Single / Multi-GPU compatible | |
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### Training Data |
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Fine-tuned using supervised instruction tuning (SFT) on: |
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- Enterprise QA datasets |
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- Task reasoning + tool usage instructions |
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- RAG-style retrieval prompts |
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- Business reports & structured communication |
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- Korean–English bilingual QA and translation |
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- Synthetic instructions with safety curation |
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--- |
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## Secure On-Premise Deployment |
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Vayne-V1 is built for **enterprise AI inside your firewall**. |
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✅ No external API dependency |
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✅ Compatible with **offline environments** |
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✅ Proven for secure deployments |
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--- |
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## MCP (Model Context Protocol) Integration |
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Vayne-V1 supports **MCP-based agent tooling**, making it easy to integrate tool-use AI. |
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Works seamlessly with: |
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* Claude MCP-compatible agent systems |
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* Local agent runtimes |
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* JSON structured execution |
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--- |
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## RAG Compatibility |
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Designed for **hybrid reasoning + retrieval**. |
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✅ Works with FAISS, Chroma, Elasticsearch |
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✅ Handles long-context document QA |
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✅ Ideal for enterprise knowledge bases |
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--- |
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## Quick Start |
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```bash |
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pip install transformers peft accelerate bitsandbytes |
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``` |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import torch |
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model_name = "PoSTMEDIA/Vayne-V1" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_name, |
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torch_dtype=torch.float16, |
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device_map="auto" |
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) |
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prompt = "Explain the benefits of private AI for enterprise security." |
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device) |
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outputs = model.generate(**inputs, max_length=256) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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``` |
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--- |
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## Use Cases |
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✅ Internal enterprise AI assistant |
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✅ Private AI document analysis |
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✅ Business writing (reports, proposals, strategy) |
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✅ AI automation agents |
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✅ Secure RAG search systems |
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--- |
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## Safety & Limitations |
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* Not intended for medical, legal, or financial decision-making |
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* May occasionally generate hallucinations |
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* Use human validation for critical outputs |
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* Recommended: enable output guardrails for production |
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--- |
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## Citation |
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```bibtex |
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@misc{vayne2025, |
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title={Vayne-V1: Private On-Premise LLM Optimized for Agents and RAG}, |
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author={PoSTMEDIA AI Lab}, |
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year={2025}, |
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publisher={Hugging Face} |
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} |
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``` |
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--- |
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## Contact |
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**PoSTMEDIA AI Lab** |
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📧 [dev.postmedia@gmail.com](mailto:dev.postmedia@gmail.com) |
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🌐 [https://postmedia.ai](https://postmedia.ai) |
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🌐 [https://postmedia.co.kr](https://postmedia.co.kr) |
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--- |
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