Instructions to use davidx08/atithi-ai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use davidx08/atithi-ai with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="davidx08/atithi-ai")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("davidx08/atithi-ai")
model = AutoModelForCausalLM.from_pretrained("davidx08/atithi-ai", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use davidx08/atithi-ai with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf davidx08/atithi-ai
# Run inference directly in the terminal:
llama cli -hf davidx08/atithi-ai

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf davidx08/atithi-ai
# Run inference directly in the terminal:
llama cli -hf davidx08/atithi-ai

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 davidx08/atithi-ai
# Run inference directly in the terminal:
./llama-cli -hf davidx08/atithi-ai

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 davidx08/atithi-ai
# Run inference directly in the terminal:
./build/bin/llama-cli -hf davidx08/atithi-ai

Use Docker

docker model run hf.co/davidx08/atithi-ai

LM Studio
Jan

vLLM

How to use davidx08/atithi-ai with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "davidx08/atithi-ai"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "davidx08/atithi-ai",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/davidx08/atithi-ai

SGLang

How to use davidx08/atithi-ai with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "davidx08/atithi-ai" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "davidx08/atithi-ai",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "davidx08/atithi-ai" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "davidx08/atithi-ai",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use davidx08/atithi-ai with Ollama:
```
ollama run hf.co/davidx08/atithi-ai
```
Unsloth Desktop
Docker Model Runner
How to use davidx08/atithi-ai with Docker Model Runner:
```
docker model run hf.co/davidx08/atithi-ai
```

Lemonade

How to use davidx08/atithi-ai with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull davidx08/atithi-ai

Run and chat with the model

lemonade run user.atithi-ai-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

davidx08 commited on 23 days ago

Commit

9091d3b

verified ·

1 Parent(s): 31a7fb4

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +31 -10

README.md CHANGED Viewed

@@ -5,25 +5,46 @@ tags:
 - travel
 - tourism
 - india
 - nexuzy-lab
 - gguf
-- restaurants
 language:
 - en
 ---
 # 🇮🇳 Atithi AI - India's Digital Travel Companion
-Developed by **David** at **Nexuzy Lab** (**DEVIL ONE PVT LTD**).
 ## 🚀 Project Overview
-Atithi AI is a specialized LLM for the Indian travel ecosystem, integrating railways, airlines, 27,000+ restaurants, and local tourism spots.
-## 👤 Developer Information
-- **Lead:** David (david@nexuzy.in)
-- **Company:** [Nexuzy Lab](https://nexuzy.in/index.php)
-- **Parent Conglomerate:** [DEVIL ONE PVT LTD](https://devilone.in)
-## 📂 Contents
-- `model/`: Standalone merged weights.
-- `atithi-ai-v1.gguf`: 8-bit quantized model for local/mobile use.

 - travel
 - tourism
 - india
+- hotels
+- restaurants
+- weather
+- railways
+- flights
 - nexuzy-lab
 - gguf
+- lora
+- nexuzy
+- devil-one
 language:
 - en
+pipeline_tag: text-generation
+library_name: transformers
 ---
 # 🇮🇳 Atithi AI - India's Digital Travel Companion
+<p align="center">
+  <img src="atitihi_logo.png" width="300" alt="Atithi AI Logo">
+</p>
+Atithi AI is an India-focused travel, hotel, restaurant, and local discovery assistant developed by **David** at **Nexuzy Lab** (Research division of **DEVIL ONE PVT LTD**).
 ## 🚀 Project Overview
+Fine-tuned on 173,000+ records covering Indian tourism, 27,000+ restaurants, railways, flights, and bus routes. Designed for local planning and localized information.
+## 👤 Developer & Company Information
+- **Lead Developer:** David ([david@nexuzy.in](mailto:david@nexuzy.in))
+- **Organization:** Nexuzy Lab ([nexuzylab@gmail.com](mailto:nexuzylab@gmail.com))
+- **Parent Company:** DEVIL ONE PVT LTD ([https://devilone.in](https://devilone.in))
+- **Official Website:** [https://nexuzy.in/index.php](https://nexuzy.in/index.php)
+- **GitHub:** [https://github.com/david0154](https://github.com/david0154)
+## 📂 Model Variants
+- **Full Model:** Merged standalone weights for use with `transformers`.
+- **GGUF Version:** 8-bit quantized file (`atithi-ai-v1.gguf`) for mobile/edge/local deployment via llama.cpp.
+## 💡 Features
+- Knowledge of 27,000+ Indian restaurants.
+- Indian Railways, Flight schedules, and Bus route context.
+- Tourism destination discovery and budget hotel assistance.
+- Optimized for compact, fast inference.