update

dataset-card.yaml

@@ -0,0 +1,19 @@
+---
+title: MSxGPT Dataset
+tags:
+  - language modeling
+  - question answering
+license: CC-BY-4.0
+size: 8.4MB
+languages:
+  - en
+multilinguality:
+  - monolingual
+references:
+  - title: "ChatGPT Retrieval Plugin Repository"
+    link: "https://github.com/MapleSage/chatgpt-retrieval-plugin"
+  - title: "Pinecone Langchain Chunking Notebook"
+    link: "https://github.com/pinecone-io/examples/blob/master/generation/langchain/handbook/xx-langchain-chunking.ipynb"
+  - title: "Pinecone Prompt Engineering Notebook"
+    link: "https://github.com/pinecone-io/examples/blob/master/generation/prompt-engineering.ipynb"
+---

pinecone-trans.py

@@ -1,12 +1,18 @@
 from transformers import AutoTokenizer, AutoModel
 import torch
+import json
+from transformers import GPT2Tokenizer
 
+tokenizer = GPT2Tokenizer.from_pretrained("MapleSage/gpt2-small")
+
+with open('train.jsonl', 'r') as file:
+    data = [json.loads(line) for line in file]
 # Initialize the tokenizer and model
 tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/bert-base-nli-mean-tokens")
 model = AutoModel.from_pretrained("sentence-transformers/bert-base-nli-mean-tokens")
 
 # Assuming your data is in a list called data
-with open("train.jsonl", "r") as file:
+with open('train.jsonl', 'r') as file:
     data = [json.loads(line) for line in file]
 
 # Process the data