adding model card

README.md

@@ -4,12 +4,13 @@ Introducing TenyxChat, a series of ChatGPT-like models trained to function as us
 
 We fine-tune [Openchat-3.5](https://arxiv.org/pdf/2309.11235.pdf) with our proprietary approach ([blog](https://www.tenyx.com/post/forgetting-and-toxicity-in-llms-a-deep-dive-on-fine-tuning-methods), [service](https://www.tenyx.com/fine-tuning)), which shows an increase in [MT-Bench](https://arxiv.org/abs/2306.05685), without a drop in performance of the model on other benchmarks. Our approach aims to mitigate forgetting in LLMs in a computationally efficient manner, thereby enabling continual fine-tuning capabilities without altering the pre-trained output distribution. TenyxChat-7B-v1 was trained using eight A100s (80GB) for two hours, with a training setup obtained from HuggingFaceH4 ([GitHub](https://github.com/huggingface/alignment-handbook)).
 
-# Model details
+---
+model_type: Fine-tuned 7B model for chat.
+license: {apache-2.0} 
+base_model: {openchat/openchat_3.5} 
+demo: [Hugging Face Spaces](https://huggingface.co/spaces/tenyx/TenyxChat-7B-v1)
+---
 
-- Model type: Fine-tuned 7B model for chat.
-- License: Apache 2.0
-- Base model: OpenChat 3.5 ([https://huggingface.co/openchat/openchat_3.5](https://huggingface.co/openchat/openchat_3.5))
-- Demo: Hugging face space
 
 ## Usage