Upload README.md

README.md

@@ -4,17 +4,17 @@ Base model: mistralai/Mistral-7B-v0.1\
 pipeline_tag: text-generation\
 ---\
 Description: Topic identification from a news article, with synthetic explanations.\
-Original dataset: https://huggingface.co/datasets/ag_news\
+Original dataset: agnews_explained \
 ---\
-Try querying this adapter for free in Lora Land at https://predibase.com/lora-land!\
+Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
 The adapter_category is Explanation and the name is News Topic Identification Explained (ag_news)\
 ---\
 Sample input: Below is a news article. Please classify it under one of the following classes (World, Business, Sports, Sci/Tech) and provide a reasonable coherent explanation for why the article is classified as such. Please format your response as a JSON payload.\n\n### Article: US poverty rate climbs, along with number lacking health coverage (AFP) AFP - The number of Americans living in poverty or without health insurance grew last year, a government survey showed, adding potential dynamite in the battle for the White House.\n\n### JSON Response\
 ---\
 Sample output: {"text_label": "World", "explanation": "The article is classified as 'World' because it discusses the poverty rate and lack of health coverage in the United States. Although it is a domestic issue, it has potential implications for the upcoming presidential election, making it relevant to a global audience."}\
 ---\
-Try using this adapter yourself! \
- ```
+Try using this adapter yourself!\
+```
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 model_id = "mistralai/Mistral-7B-v0.1"