Fix a couple of typos and add some metadata tags

cc

@nielsr



@RaushanTurganbay

README.md

@@ -1,6 +1,14 @@
 ---
+language:
+- en
 library_name: transformers
-tags: []
+license: apache-2.0
+pipeline_tag: video-text-to-text
+datasets:
+- liuhaotian/LLaVA-Pretrain
+- liuhaotian/LLaVA-Instruct-150K
+- luoruipu1/Valley-Instruct-65k
+- lmms-lab/VideoChatGPT
 ---
 
 # Model Card for Video-LLaVa
@@ -10,11 +18,11 @@ tags: []
 
 
 **Model type:**
-Video-LLaVA is an open-source multomodal model trained by fine-tuning LLM on multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture.
+Video-LLaVA is an open-source multimodal model trained by fine-tuning an LLM on multimodal instruction-following data. It is an auto-regressive language model, based on the transformer architecture.
 Base LLM: [lmsys/vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5)
 
 **Model Description:**
-The model can generate interleaving images and videos, despite the absence of image-video pairs in the dataset. Video-LLaVa is uses an encoder trained for unified visual representation through alignment prior to projection.
+The model can generate text from interleaving images and videos, despite the absence of image-video pairs in the dataset. Video-LLaVa uses an encoder trained for unified visual representation through alignment prior to projection.
 Extensive experiments demonstrate the complementarity of modalities, showcasing significant superiority when compared to models specifically designed for either images or videos.
 
 <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/videollava_example.png"
@@ -103,8 +111,8 @@ print(processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_to
 
 
 ## 👍 Acknowledgement
-* [LLaVA](https://github.com/haotian-liu/LLaVA) The codebase we built upon and it is an efficient large language and vision assistant.
-* [Video-ChatGPT](https://github.com/mbzuai-oryx/Video-ChatGPT) Great job contributing the evaluation code and dataset.
+* [LLaVA](https://github.com/haotian-liu/LLaVA) The codebase we built upon, LlaVA is an efficient large language model and vision assistant.
+* [Video-ChatGPT](https://github.com/mbzuai-oryx/Video-ChatGPT) We are grateful for the contribution of the evaluation code and dataset.
 
 ## 🔒 License
 * The majority of this project is released under the Apache 2.0 license as found in the [LICENSE](https://github.com/PKU-YuanGroup/Video-LLaVA/blob/main/LICENSE) file.