Upload hlm-dataset-README.md

hlm-dataset-README.md

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+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
+{}
+---
+
+# Dataset Card for `hlm-paraphrase-multilingual-mpnet-base-v2`
+
+### Dataset Summary
+
+Chromadb vectorstore for 红楼梦, created with 
+```
+import os
+from langchain.document_loaders import TextLoader
+from langchain.embeddings import SentenceTransformerEmbeddings
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import Chroma
+
+model_name = 'paraphrase-multilingual-mpnet-base-v2'
+embedding = SentenceTransformerEmbeddings(model_name=model_name)
+
+url = 'https://raw.githubusercontent.com/ffreemt/multilingual-dokugpt/master/docs/hlm.txt'
+os.system(f'wget -c {url}')
+doc = TextLoader('hlm.txt').load()
+
+text_splitter = RecursiveCharacterTextSplitter(
+    separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""],
+    chunk_size=620,
+    chunk_overlap=60,
+    length_function=len
+)
+
+doc_chunks = text_splitter.split_documents(doc)
+client_settings = Settings(chroma_db_impl="duckdb+parquet", anonymized_telemetry=False, persist_directory='db')
+
+# takes 8-20 minutes on CPU
+vectorstore = Chroma.from_documents(
+    documents=doc_chunks,
+    embedding=embedding,
+    persist_directory='db',
+    client_settings=client_settings,
+)
+vectorstore.persist()
+```
+
+### How to use
+
+Download the files to a local directory, e.g., `db`
+
+
+```python
+from langchain.embeddings import SentenceTransformerEmbeddings
+from langchain.vectorstores import Chroma
+from chromadb.config import Settings
+
+model_name = 'paraphrase-multilingual-mpnet-base-v2'
+embedding = SentenceTransformerEmbeddings(model_name=model_name)
+
+path_to_db_parent = '...'
+client_settings = Settings(chroma_db_impl="duckdb+parquet", anonymized_telemetry=False, persist_directory=f'{path_to_db_parent}/db')
+
+db = Chroma(
+    # persist_directory='docs',
+    embedding_function=embedding,
+    client_settings=client_settings,
+)
+
+res = db.search("红楼梦主线", search_type="similarity", k=2)
+print(res)
+# [Document(page_content='通灵宝玉正面图式\u3000通灵宝玉反面图式\n\n\n\n玉宝灵通\u3000\u3000\u3000\u3000\u3000三二一\n\n仙莫\u3000\u3000\u3000\u3000\u3000\u3000知疗除\n\n寿失\u3000\u3000\u3000\u3000\u3000\u3000祸冤邪\n\n恒莫\u3000\u3000\u3000\u3000\u3000\u3000福疾崇\n\n昌忘\n\n\n\n宝钗看毕，【甲戌双行。。。
+```