Instructions to use NeuroBridge/Chanakya-7B-v0.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use NeuroBridge/Chanakya-7B-v0.5 with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("NeuroBridge/Chanakya-7B-v0.5", dtype="auto")

llama-cpp-python

How to use NeuroBridge/Chanakya-7B-v0.5 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="NeuroBridge/Chanakya-7B-v0.5",
	filename="Chanakya-7B-v0.5-GGUF.F16.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use NeuroBridge/Chanakya-7B-v0.5 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf NeuroBridge/Chanakya-7B-v0.5:F16
# Run inference directly in the terminal:
llama-cli -hf NeuroBridge/Chanakya-7B-v0.5:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf NeuroBridge/Chanakya-7B-v0.5:F16
# Run inference directly in the terminal:
llama-cli -hf NeuroBridge/Chanakya-7B-v0.5: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 NeuroBridge/Chanakya-7B-v0.5:F16
# Run inference directly in the terminal:
./llama-cli -hf NeuroBridge/Chanakya-7B-v0.5: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 NeuroBridge/Chanakya-7B-v0.5:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf NeuroBridge/Chanakya-7B-v0.5:F16

Use Docker

docker model run hf.co/NeuroBridge/Chanakya-7B-v0.5:F16

LM Studio
Jan
Ollama
How to use NeuroBridge/Chanakya-7B-v0.5 with Ollama:
```
ollama run hf.co/NeuroBridge/Chanakya-7B-v0.5:F16
```

Unsloth Studio

How to use NeuroBridge/Chanakya-7B-v0.5 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 NeuroBridge/Chanakya-7B-v0.5 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 NeuroBridge/Chanakya-7B-v0.5 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for NeuroBridge/Chanakya-7B-v0.5 to start chatting

Atomic Chat new
Docker Model Runner
How to use NeuroBridge/Chanakya-7B-v0.5 with Docker Model Runner:
```
docker model run hf.co/NeuroBridge/Chanakya-7B-v0.5:F16
```

Lemonade

How to use NeuroBridge/Chanakya-7B-v0.5 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull NeuroBridge/Chanakya-7B-v0.5:F16

Run and chat with the model

lemonade run user.Chanakya-7B-v0.5-F16

List all available models

lemonade list

Chanakya-7B-v0.5 / README.md

Garvitk

Update README.md

bce2ecf verified about 2 years ago

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	---
	language:
	- en
	- hi
	license: apache-2.0
	tags:
	- text-generation-inference
	- transformers
	- mistral
	- gguf
	- open-aditi
	- hindi
	- india
	- hinglish
	base_model: manishiitg/open-aditi-hi-v2
	---

	Model Card

	Model Name: Chanakya-7B-v0.5

	Description: This LLM (Language Model) developed by NeuroBridge Tech is a powerful tool for natural language processing tasks. Trained on Hindi, English, and Hinglish datasets, it excels in understanding context, generating responses, and providing tailored assistance in multiple languages.

	Developed by: NeuroBridge Tech

	License: Apache-2.0

	Fine-tuned from: [manishiitg/open-aditi-hi-v2](https://huggingface.co/manishiitg/open-aditi-hi-v2)

	Contact us:
	For inquiries about our custom fine-tuned models or other inquiries, please contact:
	Email: contact@neurobridge.tech
	Website: [neurobridge.tech](https://neurobridge.tech)
	![Neurobridge Tech Logo](https://neurobridge.tech/static/media/logo01.ed4c9e7183b7efbcadc1.png)


	#### About GGUF:

	GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.

	Here is an incomplete list of clients and libraries that are known to support GGUF:

	* [llama.cpp](https://github.com/ggerganov/llama.cpp). The source project for GGUF. Offers a CLI and a server option.
	* [text-generation-webui](https://github.com/oobabooga/text-generation-webui), the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
	* [KoboldCpp](https://github.com/LostRuins/koboldcpp), a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
	* [GPT4All](https://gpt4all.io/index.html), a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
	* [LM Studio](https://lmstudio.ai/), an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023.
	* [LoLLMS Web UI](https://github.com/ParisNeo/lollms-webui), a great web UI with many interesting and unique features, including a full model library for easy model selection.
	* [Faraday.dev](https://faraday.dev/), an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
	* [llama-cpp-python](https://github.com/abetlen/llama-cpp-python), a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
	* [candle](https://github.com/huggingface/candle), a Rust ML framework with a focus on performance, including GPU support, and ease of use.
	* [ctransformers](https://github.com/marella/ctransformers), a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models.