Change model_name_or_path and model_name params to model in exa…

…mple code blocks (#134)
deepset-ai · Jan 18, 2024 · 61886f4 · 61886f4
1 parent 0d8bb9a
commit 61886f4
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Showing 4 changed files with 9 additions and 9 deletions.
diff --git a/integrations/elasticsearch-document-store.md b/integrations/elasticsearch-document-store.md
@@ -68,7 +68,7 @@ from haystack.components.writers import DocumentWriter
 document_store = ElasticsearchDocumentStore(hosts = "http://localhost:9200")
 converter = TextFileToDocument()
 splitter = DocumentSplitter()
-doc_embedder = SentenceTransformersDocumentEmbedder(model_name_or_path="sentence-transformers/multi-qa-mpnet-base-dot-v1")
+doc_embedder = SentenceTransformersDocumentEmbedder(model="sentence-transformers/multi-qa-mpnet-base-dot-v1")
 writer = DocumentWriter(document_store)
 
 indexing_pipeline = Pipeline()
@@ -96,13 +96,13 @@ from haystack.pipeline import Pipeline
 from haystack.components.embedders import SentenceTransformersTextEmbedder 
 from elasticsearch_haystack.embedding_retriever import ElasticsearchEmbeddingRetriever
 
-model_name_or_path = "sentence-transformers/multi-qa-mpnet-base-dot-v1"
+model = "sentence-transformers/multi-qa-mpnet-base-dot-v1"
 
 document_store = ElasticsearchDocumentStore(hosts = "http://localhost:9200")
 
 
 retriever = ElasticsearchEmbeddingRetriever(document_store=document_store)
-text_embedder = SentenceTransformersTextEmbedder(model_name_or_path=model_name_or_path)
+text_embedder = SentenceTransformersTextEmbedder(model=model)
 
 query_pipeline = Pipeline()
 query_pipeline.add_component("text_embedder", text_embedder)

diff --git a/integrations/huggingface.md b/integrations/huggingface.md
@@ -62,7 +62,7 @@ documents = [Document(content="My name is Wolfgang and I live in Berlin"),
              Document(content="Germany has many big cities")]
 
 indexing_pipeline = Pipeline()
-indexing_pipeline.add_component("embedder", SentenceTransformersDocumentEmbedder(model_name_or_path="sentence-transformers/all-MiniLM-L6-v2"))
+indexing_pipeline.add_component("embedder", SentenceTransformersDocumentEmbedder(model="sentence-transformers/all-MiniLM-L6-v2"))
 indexing_pipeline.add_component("writer", DocumentWriter(document_store=document_store))
 indexing_pipeline.connect("embedder", "writer")
 indexing_pipeline.run({
@@ -128,7 +128,7 @@ document_store = InMemoryDocumentStore()
 document_store.write_documents(docs)
 
 retriever = InMemoryBM25Retriever(document_store = document_store)
-ranker = TransformersSimilarityRanker(model_name_or_path="cross-encoder/ms-marco-MiniLM-L-6-v2")
+ranker = TransformersSimilarityRanker(model="cross-encoder/ms-marco-MiniLM-L-6-v2")
 
 document_ranker_pipeline = Pipeline()
 document_ranker_pipeline.add_component(instance=retriever, name="retriever")
@@ -160,7 +160,7 @@ document_store = InMemoryDocumentStore()
 document_store.write_documents(docs)
 
 retriever = InMemoryBM25Retriever(document_store = document_store)
-reader = ExtractiveReader(model_name_or_path="deepset/roberta-base-squad2-distilled")
+reader = ExtractiveReader(model="deepset/roberta-base-squad2-distilled")
 
 extractive_qa_pipeline = Pipeline()
 extractive_qa_pipeline.add_component(instance=retriever, name="retriever")

diff --git a/integrations/openai.md b/integrations/openai.md
@@ -61,7 +61,7 @@ documents = [Document(content="My name is Wolfgang and I live in Berlin"),
              Document(content="Germany has many big cities")]
 
 indexing_pipeline = Pipeline()
-indexing_pipeline.add_component("embedder", OpenAIDocumentEmbedder(api_key="OPENAI_API_KEY", model_name="text-embedding-ada-002"))
+indexing_pipeline.add_component("embedder", OpenAIDocumentEmbedder(api_key="OPENAI_API_KEY", model="text-embedding-ada-002"))
 indexing_pipeline.add_component("writer", DocumentWriter(document_store=document_store))
 indexing_pipeline.connect("embedder", "writer")
 
@@ -128,7 +128,7 @@ from haystack.document_stores import InMemoryDocumentStore
 
 document_store = InMemoryDocumentStore()
 pipeline = Pipeline()
-pipeline.add_component(instance=LocalWhisperTranscriber(model_name_or_path="small"), name="transcriber")
+pipeline.add_component(instance=LocalWhisperTranscriber(model="small"), name="transcriber")
 pipeline.add_component(instance=DocumentCleaner(), name="cleaner")
 pipeline.add_component(instance=DocumentSplitter(), name="splitter")
 pipeline.add_component(instance=DocumentWriter(document_store=document_store), name="writer")

diff --git a/integrations/pinecone-document-store.md b/integrations/pinecone-document-store.md
@@ -122,7 +122,7 @@ query_pipeline = Pipeline()
 query_pipeline.add_component("text_embedder", SentenceTransformersTextEmbedder())
 query_pipeline.add_component("retriever", PineconeDenseRetriever(document_store=document_store))
 query_pipeline.add_component("prompt_builder", PromptBuilder(template=prompt_template))
-query_pipeline.add_component("generator", OpenAIGenerator(api_key=YOUR_OPENAI_KEY, model_name="gpt-4"))
+query_pipeline.add_component("generator", OpenAIGenerator(api_key=YOUR_OPENAI_KEY, model="gpt-4"))
 query_pipeline.connect("text_embedder.embedding", "retriever.query_embedding")
 query_pipeline.connect("retriever.documents", "prompt_builder.documents")
 query_pipeline.connect("prompt_builder", "generator")