Instructions to use gagan3012/project-code-py-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gagan3012/project-code-py-small with Transformers:

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

pipe = pipeline("text-generation", model="gagan3012/project-code-py-small")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gagan3012/project-code-py-small")
model = AutoModelForCausalLM.from_pretrained("gagan3012/project-code-py-small", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use gagan3012/project-code-py-small with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gagan3012/project-code-py-small"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gagan3012/project-code-py-small",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/gagan3012/project-code-py-small

SGLang

How to use gagan3012/project-code-py-small 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 "gagan3012/project-code-py-small" \
    --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": "gagan3012/project-code-py-small",
		"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 "gagan3012/project-code-py-small" \
        --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": "gagan3012/project-code-py-small",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use gagan3012/project-code-py-small with Docker Model Runner:
```
docker model run hf.co/gagan3012/project-code-py-small
```

gagan3012 commited on Mar 11, 2021

Commit

bd89baa

1 Parent(s): 83d33d6

Create README.md

Browse files

Files changed (1) hide show

README.md +33 -0

README.md ADDED Viewed

	@@ -0,0 +1,33 @@

+# keytotext
+Idea is to build a model which will take keywords as inputs and generate sentences as outputs.
+### Model:
+Two Models have been built:
+- Using T5-base size = 850 MB can be found here: https://huggingface.co/gagan3012/keytotext
+- Using T5-small size = 230 MB can be found here: https://huggingface.co/gagan3012/keytotext-small
+#### Usage:
+```python
+from transformers import AutoTokenizer, AutoModelWithLMHead
+tokenizer = AutoTokenizer.from_pretrained("gagan3012/keytotext-small")
+model = AutoModelWithLMHead.from_pretrained("gagan3012/keytotext-small")
+```
+### Demo:
+[![Streamlit App](https://static.streamlit.io/badges/streamlit_badge_black_white.svg)](https://share.streamlit.io/gagan3012/keytotext/app.py)
+https://share.streamlit.io/gagan3012/keytotext/app.py
+![image](https://user-images.githubusercontent.com/49101362/110660053-3b20fe80-81d4-11eb-9275-ba402134e8d9.png)
+### Example:
+['India', 'Wedding']  -> We are celebrating today in New Delhi with three wedding anniversary parties.