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Inference too slow

Hi!

Thank you for sharing your good. Its really a great help to understand langchain and LLMs.
I am running the model using NVIDIA V100 32GB ram. The model takes a lot of time to response to the questions. The size pdf document I am loading is around 1.4 MB.

Can you please comment on how to improve the response time?

Regards

run local_app.py LlamaCpp load error

models/ggml-vic13b-q5_1.bin
llama.cpp: loading model from models/ggml-vic13b-q5_1.bin
error loading model: unknown (magic, version) combination: 67676a74, 00000002; is this really a GGML file?
llama_init_from_file: failed to load model

example in test.env doesn't match if statement

In test.env, it mentions MODEL_TYPE = LlamaCpp or GPT4ALL

However, in local_app.py the if statement is as follows:

elif model_type == 'GPT4All':

This causes it to never match, as the L's are uppercase in test.env, but lowercase in the if statement.

I tried to create a branch and submit a PR for this but got 401, though that could be entirely my fault

Local Summarizer Support

Hey! Is there any way to get the summarizer working off a local LMM?

The only way I've found to use the summarizer is with an OpenAI key with gpt3.5 or gpt4.

ModuleNotFoundError: No module named 'sklearn'

This happens when running streamlit run main.py

I am using conda for a virtual env and installed the dependencies in the requirements file. I had to manually remove the pywin32 dependency since I'm on an m1 MBP and that doesn't appear to exist.

Please advise.

image

Repo is missing license

The repo is missing a license, which makes it technically a closed sourced, even though I believe it is intended to be open source. I suggest adding an MIT license

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