Update README.md

README.md

@@ -2,6 +2,7 @@
 license: mit
 datasets:
 - teapotai/synthqa
+- teapotai/teapot-chat
 language:
 - en
 - fr
@@ -14,49 +15,65 @@ tags:
 - transformers.js
 widget:
 - text: >-
-    Teapot is an open-source small language model (~800 million parameters) fine-tuned on synthetic data and optimized to run locally on resource-constrained devices such as smartphones and CPUs.
-    Teapot is trained to only answer using context from documents, reducing hallucinations.
-    Teapot can perform a variety of tasks, including hallucination-resistant Question Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction.
-    TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data generated by Deepseek v3
-    TeapotLLM can be hosted on low-power devices with as little as 2GB of CPU RAM such as a Raspberry Pi.
-    Teapot is a model built by and for the community.
+    Teapot is an open-source small language model (~800 million parameters)
+    fine-tuned on synthetic data and optimized to run locally on
+    resource-constrained devices such as smartphones and CPUs. Teapot is trained
+    to only answer using context from documents, reducing hallucinations. Teapot
+    can perform a variety of tasks, including hallucination-resistant Question
+    Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction.
+    TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data
+    generated by Deepseek v3 TeapotLLM can be hosted on low-power devices with
+    as little as 2GB of CPU RAM such as a Raspberry Pi. Teapot is a model built
+    by and for the community.
 
 
     What devices can teapot run on?
   example_title: Question Answering
 - text: >-
-    Teapot is an open-source small language model (~800 million parameters) fine-tuned on synthetic data and optimized to run locally on resource-constrained devices such as smartphones and CPUs.
-    Teapot is trained to only answer using context from documents, reducing hallucinations.
-    Teapot can perform a variety of tasks, including hallucination-resistant Question Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction.
-    TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data generated by Deepseek v3
-    TeapotLLM can be hosted on low-power devices with as little as 2GB of CPU RAM such as a Raspberry Pi.
-    Teapot is a model built by and for the community.
+    Teapot is an open-source small language model (~800 million parameters)
+    fine-tuned on synthetic data and optimized to run locally on
+    resource-constrained devices such as smartphones and CPUs. Teapot is trained
+    to only answer using context from documents, reducing hallucinations. Teapot
+    can perform a variety of tasks, including hallucination-resistant Question
+    Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction.
+    TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data
+    generated by Deepseek v3 TeapotLLM can be hosted on low-power devices with
+    as little as 2GB of CPU RAM such as a Raspberry Pi. Teapot is a model built
+    by and for the community.
 
 
     Tell me about teapotllm 
   example_title: Summarization Answering
 - text: >-
-    Teapot is an open-source small language model (~800 million parameters) fine-tuned on synthetic data and optimized to run locally on resource-constrained devices such as smartphones and CPUs.
-    Teapot is trained to only answer using context from documents, reducing hallucinations.
-    Teapot can perform a variety of tasks, including hallucination-resistant Question Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction.
-    TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data generated by Deepseek v3
-    TeapotLLM can be hosted on low-power devices with as little as 2GB of CPU RAM such as a Raspberry Pi.
-    Teapot is a model built by and for the community.
+    Teapot is an open-source small language model (~800 million parameters)
+    fine-tuned on synthetic data and optimized to run locally on
+    resource-constrained devices such as smartphones and CPUs. Teapot is trained
+    to only answer using context from documents, reducing hallucinations. Teapot
+    can perform a variety of tasks, including hallucination-resistant Question
+    Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction.
+    TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data
+    generated by Deepseek v3 TeapotLLM can be hosted on low-power devices with
+    as little as 2GB of CPU RAM such as a Raspberry Pi. Teapot is a model built
+    by and for the community.
 
 
     Extract the number of parameters
   example_title: Information Extraction
 - text: >-
-    Teapot is an open-source small language model (~800 million parameters) fine-tuned on synthetic data and optimized to run locally on resource-constrained devices such as smartphones and CPUs.
-    Teapot is trained to only answer using context from documents, reducing hallucinations.
-    Teapot can perform a variety of tasks, including hallucination-resistant Question Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction.
-    TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data generated by Deepseek v3
-    TeapotLLM can be hosted on low-power devices with as little as 2GB of CPU RAM such as a Raspberry Pi.
-    Teapot is a model built by and for the community.
+    Teapot is an open-source small language model (~800 million parameters)
+    fine-tuned on synthetic data and optimized to run locally on
+    resource-constrained devices such as smartphones and CPUs. Teapot is trained
+    to only answer using context from documents, reducing hallucinations. Teapot
+    can perform a variety of tasks, including hallucination-resistant Question
+    Answering (QnA), Retrieval-Augmented Generation (RAG), and JSON extraction.
+    TeapotLLM is a fine tune of flan-t5-large that was trained on synthetic data
+    generated by Deepseek v3 TeapotLLM can be hosted on low-power devices with
+    as little as 2GB of CPU RAM such as a Raspberry Pi. Teapot is a model built
+    by and for the community.
 
 
     How many parameters is Deepseek? 
-  example_title: Hallucination Resistance 
+  example_title: Hallucination Resistance
 base_model:
 - google/flan-t5-large
 pipeline_tag: text2text-generation