Instructions to use curious-techie/Vritya-Tiny-163M-HF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use curious-techie/Vritya-Tiny-163M-HF with Transformers:

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

pipe = pipeline("text-generation", model="curious-techie/Vritya-Tiny-163M-HF", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("curious-techie/Vritya-Tiny-163M-HF", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use curious-techie/Vritya-Tiny-163M-HF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "curious-techie/Vritya-Tiny-163M-HF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "curious-techie/Vritya-Tiny-163M-HF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/curious-techie/Vritya-Tiny-163M-HF

SGLang

How to use curious-techie/Vritya-Tiny-163M-HF 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 "curious-techie/Vritya-Tiny-163M-HF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "curious-techie/Vritya-Tiny-163M-HF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "curious-techie/Vritya-Tiny-163M-HF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "curious-techie/Vritya-Tiny-163M-HF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use curious-techie/Vritya-Tiny-163M-HF with Docker Model Runner:
```
docker model run hf.co/curious-techie/Vritya-Tiny-163M-HF
```

Vritya-Tiny-163M-HF / tokenizer.json

curious-techie

Add Transformers export (model.safetensors, config, custom code, tokenizer)

16df927 verified 25 days ago

raw

history contribute delete

3.56 MB

File too large to display, you can check the raw version instead.