Update README.md

README.md

@@ -1,49 +1,20 @@
 ---
 inference: false
 license: apache-2.0
-library_name: m
+library_name: llava
 pipeline_tag: image-text-to-text
 tags:
-- m
+- llava
+- slora
+- taqi
+- image-text-to-text
 ---
 
 <br>
 <br>
 
-# LLaVA Model Card
+# LLava Model Card
 
 ## Model details
 
-**Model type:**
-LLaVA is an open-source chatbot trained by fine-tuning LLM on multimodal instruction-following data.
-It is an auto-regressive language model, based on the transformer architecture.
-Base LLM: [NousResearch/Nous-Hermes-2-Yi-34B](https://huggingface.co/NousResearch/Nous-Hermes-2-Yi-34B)
-
-**Model date:**
-LLaVA-v1.6-34B was trained in December 2023.
-
-**Paper or resources for more information:**
-https://llava-vl.github.io/
-
-## License
-[NousResearch/Nous-Hermes-2-Yi-34B](https://huggingface.co/NousResearch/Nous-Hermes-2-Yi-34B) license.
-
-**Where to send questions or comments about the model:**
-https://github.com/haotian-liu/LLaVA/issues
-
-## Intended use
-**Primary intended uses:**
-The primary use of LLaVA is research on large multimodal models and chatbots.
-
-**Primary intended users:**
-The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.
-
-## Training dataset
-- 558K filtered image-text pairs from LAION/CC/SBU, captioned by BLIP.
-- 158K GPT-generated multimodal instruction-following data.
-- 500K academic-task-oriented VQA data mixture.
-- 50K GPT-4V data mixture.
-- 40K ShareGPT data.
-
-## Evaluation dataset
-A collection of 12 benchmarks, including 5 academic VQA benchmarks and 7 recent benchmarks specifically proposed for instruction-following LMMs.
+CREATOR : MUHAMMADTAQI