Update README.md

README.md

@@ -18,37 +18,32 @@ tags:
   <img src="https://github.com/mkturkcan/femtovlm/blob/main/assets/logo.png?raw=true"  width="180" />
 </p>
 <h1 align="center">
-  <p>mehmetkeremturkcan/DeepSeek-LLaVA-Instruct</p>
+  <p>mehmetkeremturkcan/FemtoVLM-Tiny</p>
 </h1>
 <h3 align="center">
-  <p>DeepSeer: Vision Language Models with Reasoning</p>
+  <p>FemtoVLM: Tiniest Vision Language Models</p>
 </h3>
 
-Vision language models with chain-of-thought reasoning are just starting to emerge. This is a proof-of-concept to train a vision model with thinking-enabled chat templates based on DeepSeek-R1 models.
-
-Note that this model will not always use thinking tokens, due to the current lack of high-quality CoT data in non-science contexts.
+FemtoVLM is the smallest visual question answering/captioning model in the world. It accepts image and text inputs to produce text outputs. It's designed for efficiency. FemtoVLM can answer questions about images and describe visual content. Its lightweight architecture makes it suitable for on-device applications while maintaining strong performance.
 
+FemtoVLM comes in three sizes: 116M (femto), 143M (tiny), 160M (base), 225M (dino). All models are trained for image captioning and question answering in real-world contexts. FemtoVLM cannot perform optical character recognition (OCR), multi-turn question-answering, or scientific question answering.
 ## Setup
 ```bash
 pip install git+https://github.com/facebookresearch/schedule_free.git
 pip install peft
 git clone https://github.com/mkturkcan/seers.git
 cd seers/seers/
-git clone https://huggingface.co/mehmetkeremturkcan/DeepSeek-LLaVA-Instruct
+git clone https://huggingface.co/mehmetkeremturkcan/FemtoVLM-Tiny
 ```
 ## Test
 Run, in the seers/seers folder,
 ```bash
-python predict_llava.py
+python femtovlm_inference.py
 ```
 
 ## Train
 
 [seers](https://github.com/mkturkcan/seers) training code is public! Run
 ```bash
-python train_cot_mixed.py
+python femtovlm_train.py
 ```
-
-## Training Details
-This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Llama-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Llama-8B) on the [5CD-AI/LLaVA-CoT-o1-Instruct](https://huggingface.co/datasets/5CD-AI/LLaVA-CoT-o1-Instruct) dataset.
-It has been trained using [seers](https://github.com/mkturkcan/seers).