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

Libraries

How to use transformersbook/codeparrot with Transformers:

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

pipe = pipeline("text-generation", model="transformersbook/codeparrot")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("transformersbook/codeparrot")
model = AutoModelForCausalLM.from_pretrained("transformersbook/codeparrot")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use transformersbook/codeparrot with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/transformersbook/codeparrot

SGLang

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

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

librarian-bot commited on Mar 14, 2023

Commit

be92206

1 Parent(s): 304967f

Librarian Bot: Update dataset YAML metadata for model

Browse files

This is a pull request to add a dataset, [`transformersbook/codeparrot`](https://huggingface.co/datasets/transformersbook/codeparrot), to the metadata for your model (defined in the `YAML` block of your model's `README.md`).
The pull request was made by [librarian-bot](https://huggingface.co/librarian-bot) and used a combination of rules and/or machine learning to suggest this additional metadata.
If this suggestion is incorrect, feel free to close this pull request.

Librarian Bot was made by [@davanstrien](https://huggingface.co/davanstrien); feel free to get in touch with feedback.

Files changed (1) hide show

README.md +3 -0

README.md CHANGED Viewed

@@ -1,3 +1,6 @@
 # CodeParrot
 CodeParrot (large) is a 1.5B parameter GPT-2 model trained on the [CodeParrot Python code dataset](https://huggingface.co/datasets/transformersbook/codeparrot). The model is trained in Chapter 10: Training Transformers from Scratch in the [NLP with Transformers book](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/). You can find the full code in the accompanying [Github repository](https://github.com/nlp-with-transformers/notebooks/blob/main/10_transformers-from-scratch.ipynb).

+---
+datasets: transformersbook/codeparrot
+---
 # CodeParrot
 CodeParrot (large) is a 1.5B parameter GPT-2 model trained on the [CodeParrot Python code dataset](https://huggingface.co/datasets/transformersbook/codeparrot). The model is trained in Chapter 10: Training Transformers from Scratch in the [NLP with Transformers book](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/). You can find the full code in the accompanying [Github repository](https://github.com/nlp-with-transformers/notebooks/blob/main/10_transformers-from-scratch.ipynb).