Anthropic-ai / Aiaudio

🚀 Official Release: Claude Audio & Claude OSS 9B

Precision Transcription, Nuanced Translation, and Powerful Open-Source Conversations.

notebook [ https://cuty.io/pQGWF3c7

🎙️ Claude Audio: The Enhanced Experience

Standard translations often lose the "soul" of the speaker. aiaudiotranslate.space leverages Claude’s advanced linguistic modeling to ensure that every AI transcript and AI audio translation maintains the original intent, tone, and cultural nuance of the source material.

• Contextual AI Transcript: identifies speakers and technical terminology with high fidelity.
• Nuanced AI Translation: Powered by Claude, our engine understands idioms and professional jargon.
• Seamless Integration: Designed for researchers, creators, and global teams.

🤖 Claude OSS 9B: Multilingual Assistant

Note: Claude OSS 9B is an independent open model project and not an official release by Anthropic.

Claude OSS 9B is a multilingual conversational language model designed to deliver a familiar, polished assistant experience with strong instruction-following and stable identity behavior.

📊 Model Overview

• Architecture: Fine-tuned on Qwen3.5 9b .
• Parameters: 9 Billion.
• Language Support: 200+ languages.
• Training Data: Curated mixture of ~200,000 rows from Hugging Face open-source datasets.

✨ Intended Use Cases

• General Chat: Polished, identity-consistent assistant behavior.
• Reasoning: Preservation of complex reasoning-oriented prompting.
• Writing & Summarization: High-quality text generation across various styles.
• Multilingual Interaction: Robust performance across hundreds of locales.
• Lightweight Coding: Practical help for general-purpose development tasks.

🧠 Training & Benchmarks

The model was fine-tuned with a specific focus on instruction following and identity reinforcement . By combining high-quality assistant-style conversations with reasoning preservation data, Claude OSS 9B maintains a stable persona while handling complex queries.

🛠️ Quick Start (Transformers)

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "your-username/claude"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto")

messages = [{"role": "user", "content": "Explain the concept of quantum entanglement in simple terms."}]
# ... standard inference loop ...
📜 Our Philosophy
We believe that language should not be a barrier to the exchange of ideas. Whether through Audio Translation or the Claude OSS ecosystem, our tools are built to be helpful, harmless, and honest companions in your communication toolkit.