edit example

examples.py

@@ -5,23 +5,11 @@ examples = [
         "Name": "",
         "Number of parameters": "",
         "Number of token": "",
-        "Architecture": []
     },
     "Usage": {
-        "Use case": [],
-        "Licence": ""
+        "Use case": []
     }
-}""","""We introduce Mistral 7B, a 7–billion-parameter language model engineered for
-superior performance and efficiency. Mistral 7B outperforms the best open 13B
-model (Llama 2) across all evaluated benchmarks, and the best released 34B
-model (Llama 1) in reasoning, mathematics, and code generation. Our model
-leverages grouped-query attention (GQA) for faster inference, coupled with sliding
-window attention (SWA) to effectively handle sequences of arbitrary length with a
-reduced inference cost. We also provide a model fine-tuned to follow instructions,
-Mistral 7B – Instruct, that surpasses Llama 2 13B – chat model both on human and
-automated benchmarks. Our models are released under the Apache 2.0 license.
-Code: https://github.com/mistralai/mistral-src
-Webpage: https://mistral.ai/news/announcing-mistral-7b/""", True],
+}""","""We introduce NuExtract-v1.5 -- a fine-tuning of Phi-3.5-mini-instruct, which is a 3.8B parameter language model. It is trained on a private high-quality dataset for structured information extraction. It supports long documents (up to 128k token context) and several languages (English, French, Spanish, German, Portuguese, and Italian). To use the model, provide an input text and a JSON template describing the information you need to extract.""", True],
     ["""{
     "Doctor_Patient_Discussion": {
         "Initial_Observation": {