Instructions to use rnijhara-canvas/WGPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use rnijhara-canvas/WGPT with Transformers:

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

pipe = pipeline("text-generation", model="rnijhara-canvas/WGPT")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("rnijhara-canvas/WGPT")
model = AutoModelForCausalLM.from_pretrained("rnijhara-canvas/WGPT", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use rnijhara-canvas/WGPT with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/rnijhara-canvas/WGPT

SGLang

How to use rnijhara-canvas/WGPT 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 "rnijhara-canvas/WGPT" \
    --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": "rnijhara-canvas/WGPT",
		"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 "rnijhara-canvas/WGPT" \
        --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": "rnijhara-canvas/WGPT",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use rnijhara-canvas/WGPT with Docker Model Runner:
```
docker model run hf.co/rnijhara-canvas/WGPT
```

WGPT

Commit History

Upload MistralForCausalLM

da88218
verified

Roopak Nijhara commited on Jul 18, 2024

Upload tokenizer

212dc7f
verified

Roopak Nijhara commited on Jul 18, 2024

initial commit

d15e2d5
verified

Roopak Nijhara commited on Jul 18, 2024

Commit History

Upload MistralForCausalLM da88218 verified

Upload tokenizer 212dc7f verified

initial commit d15e2d5 verified

Upload MistralForCausalLM

da88218
verified

Upload tokenizer

212dc7f
verified

initial commit

d15e2d5
verified