Instructions to use techcodebhavesh/AutoDashAnalyticsV1GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use techcodebhavesh/AutoDashAnalyticsV1GGUF with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("techcodebhavesh/AutoDashAnalyticsV1GGUF", dtype="auto")

llama-cpp-python

How to use techcodebhavesh/AutoDashAnalyticsV1GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="techcodebhavesh/AutoDashAnalyticsV1GGUF",
	filename="AutoDashv1.F16.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use techcodebhavesh/AutoDashAnalyticsV1GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf techcodebhavesh/AutoDashAnalyticsV1GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf techcodebhavesh/AutoDashAnalyticsV1GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf techcodebhavesh/AutoDashAnalyticsV1GGUF:F16
# Run inference directly in the terminal:
llama-cli -hf techcodebhavesh/AutoDashAnalyticsV1GGUF:F16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf techcodebhavesh/AutoDashAnalyticsV1GGUF:F16
# Run inference directly in the terminal:
./llama-cli -hf techcodebhavesh/AutoDashAnalyticsV1GGUF:F16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf techcodebhavesh/AutoDashAnalyticsV1GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf techcodebhavesh/AutoDashAnalyticsV1GGUF:F16

Use Docker

docker model run hf.co/techcodebhavesh/AutoDashAnalyticsV1GGUF:F16

LM Studio
Jan
Ollama
How to use techcodebhavesh/AutoDashAnalyticsV1GGUF with Ollama:
```
ollama run hf.co/techcodebhavesh/AutoDashAnalyticsV1GGUF:F16
```

Unsloth Studio new

How to use techcodebhavesh/AutoDashAnalyticsV1GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for techcodebhavesh/AutoDashAnalyticsV1GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for techcodebhavesh/AutoDashAnalyticsV1GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for techcodebhavesh/AutoDashAnalyticsV1GGUF to start chatting

Docker Model Runner
How to use techcodebhavesh/AutoDashAnalyticsV1GGUF with Docker Model Runner:
```
docker model run hf.co/techcodebhavesh/AutoDashAnalyticsV1GGUF:F16
```

Lemonade

How to use techcodebhavesh/AutoDashAnalyticsV1GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull techcodebhavesh/AutoDashAnalyticsV1GGUF:F16

Run and chat with the model

lemonade run user.AutoDashAnalyticsV1GGUF-F16

List all available models

lemonade list

AutoDashAnalyticsV1GGUF

AutoDashAnalyticsV1GGUF is a powerful tool designed to automate the creation of dashboards from various databases using advanced AI techniques. This model connects to SQL databases and provides interactive data visualizations through user prompts.

Model Details

Model Name: AutoDashAnalyticsV1GGUF
Version: 1.0
Language: English
License: MIT
Tags: data-analytics, dashboard, AI, visualization

Model Description

AutoDashAnalyticsV1GGUF is developed to simplify and enhance the data analysis process for companies. It leverages a fine-tuned large language model trained on extensive datasets specifically for data analysis. The tool enables users to create detailed and interactive dashboards with minimal effort.

Features

Automated Dashboard Creation: Automatically generates dashboards from SQL databases.
Interactive Visualizations: Allows users to interact with the data through prompts.
Advanced AI Capabilities: Utilizes a fine-tuned LLM for comprehensive data analysis.
Customization: Provides options for customizing the visualizations and data representation.

Training Data

The model is trained on a diverse dataset comprising various SQL databases and data visualization examples. This ensures robust performance across different data types and structures.

Performance

AutoDashAnalyticsV1GGUF has been tested extensively to ensure high accuracy and reliability in generating dashboards. The model can handle large datasets and provide insightful visualizations efficiently.

Limitations

The model is currently optimized for Relational databases.
Future versions will include support for other database types.

License

This project is licensed under the MIT License.

Acknowledgements

We acknowledge the contributions of the open-source community and the developers who have supported this project.

Citation

If you use this model in your research, please cite it as follows: @misc{AutoDashAnalyticsV1GGUF, title = {AutoDashAnalyticsV1GGUF}, year = {2024}, publisher = {Hugging Face}, journal = {Hugging Face repository}, howpublished = {\url{https://huggingface.co/techcodebhavesh/AutoDashAnalyticsV1GGUF}} }

Downloads last month: 73

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

4-bit

16-bit

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