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All of them are used through the notebook but not installed previously.
The errors are thrown in:
datasets:
from tqdm.notebook import tqdm
import pandas as pd
from typing import Optional, List, Tuple
from datasets import Dataset
import matplotlib.pyplot as plt
pd.set_option(
"display.max_colwidth", None
) # This will be helpful when visualizing retriever outputs
langchain-community :
from langchain.vectorstores import FAISS
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.vectorstores.utils import DistanceStrategy
embedding_model = HuggingFaceEmbeddings(
model_name=EMBEDDING_MODEL_NAME,
multi_process=True,
model_kwargs={"device": "cuda"},
encode_kwargs={"normalize_embeddings": True}, # Set `True` for cosine similarity
)
KNOWLEDGE_VECTOR_DATABASE = FAISS.from_documents(
docs_processed, embedding_model, distance_strategy=DistanceStrategy.COSINE
)
ragatouille
from ragatouille import RAGPretrainedModel
RERANKER = RAGPretrainedModel.from_pretrained("colbert-ir/colbertv2.0")
The text was updated successfully, but these errors were encountered:
In the Advanced RAG on Hugging Face documentation using LangChain example, when running it on Colab, it generates some errors due to missing dependencies.
These dependencies are:
All of them are used through the notebook but not installed previously.
The errors are thrown in:
The text was updated successfully, but these errors were encountered: