Language Model Analyst
The Language Model Analyst is a Python package and Streamlit app that enables natural language generation and analysis using HuggingFace-based language models (LLMs) and OpenAI GPT-3. This package and app are designed to simplify and streamline interactions with these powerful language models.
Usage
Package: LLMAnalyst
The LLMAnalyst class allows you to interact with HuggingFace-based language models. Follow these steps to use the package:
-
Install the package:
pip install git+https://github.com/eersnington/LLMAnalyst.git # For using GPTQ models pip install auto-gptq --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/
-
Import and create an instance of LLMAnalyst:
from LLMAnalyst import LLMAnalyst llm_analyst = LLMAnalyst("TheBloke/CodeLlama-13B-Instruct-GPTQ")
-
query = "How many number of rows are there?" df = pd.read_csv("data.csv") result = llm_analyst.conversational_chat(query, df)
The OpenAIGPTAnalyst class enables interaction with the OpenAI GPT-3 model. Follow these steps to use the package:
-
Import and create an instance of OpenAIGPTAnalyst:
from LLMAnalyst import OpenAIGPTAnalyst openai_analyst = OpenAIGPTAnalyst( api_key='YOUR_OPENAI_API_KEY' )
-
Communicate with GPT-3:
query = "Calculate the mean of monthly sold data." df = pd.read_csv("data.csv") result = openai_analyst.conversational_chat(query, your_dataframe)
Metadata
Release files for llmanalyst 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| llmanalyst-0.0.1.tar.gz | 2.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| llmanalyst-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.6 kB
Release files / llmanalyst-0.0.1.tar.gz
| Download URL | llmanalyst-0.0.1.tar.gz |
|---|---|
| Size | 2.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
586a4aba597e89151cc9bddb2cb264b3077998b1cddcc38cf4c2f05b8d610a3b
|
|
BLAKE2b-256 checksum How to use checksums |
5755248cec80b0969237cb01fa9f66f283015b0cb4a0a3fc416d5a4998b9a5cf
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|
Release files / llmanalyst-0.0.1-py3-none-any.whl
| Download URL | llmanalyst-0.0.1-py3-none-any.whl |
|---|---|
| Size | 2.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
f48cc9469ba0ca95b8d3039aee029cb6ab971b8c80f387ff2272c260a75c5bcb
|
|
BLAKE2b-256 checksum How to use checksums |
8a6e65879c3a75a8ee983381c6158ad8f4757469f622473b3afc53fe6387788d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.12
|