Instructions to use Ranjan22/TextToTagGenerator_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Ranjan22/TextToTagGenerator_large with Transformers:

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

pipe = pipeline("text-generation", model="Ranjan22/TextToTagGenerator_large")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Ranjan22/TextToTagGenerator_large")
model = AutoModelForSeq2SeqLM.from_pretrained("Ranjan22/TextToTagGenerator_large", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Ranjan22/TextToTagGenerator_large with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Ranjan22/TextToTagGenerator_large"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Ranjan22/TextToTagGenerator_large",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Ranjan22/TextToTagGenerator_large

SGLang

How to use Ranjan22/TextToTagGenerator_large 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 "Ranjan22/TextToTagGenerator_large" \
    --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": "Ranjan22/TextToTagGenerator_large",
		"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 "Ranjan22/TextToTagGenerator_large" \
        --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": "Ranjan22/TextToTagGenerator_large",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Ranjan22/TextToTagGenerator_large with Docker Model Runner:
```
docker model run hf.co/Ranjan22/TextToTagGenerator_large
```

TextToTagGenerator_large

Commit History

Jul 6, 2023

14:42
Adding `safetensors` variant of this model⁠

SFconvertbot

3f1421e

May 15, 2023

11:02
Create README.md

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initial commit

Ranjan22

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Commit History

Jul 6, 2023

Adding `safetensors` variant of this model⁠

May 15, 2023

Create README.md

Training in progress, step 19200

Training in progress, step 17280

Training in progress, step 15360

Training in progress, step 13440

Training in progress, step 11520

Training in progress, step 9600

Training in progress, step 7680

Training in progress, step 5760

Training in progress, step 3840

Training in progress, step 1920

initial commit