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
```

codeparrot

Commit History

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lvwerra HF Staff commited on Aug 21, 2021

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leandro von werra commited on Aug 11, 2021

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leandro von werra commited on Aug 11, 2021

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system HF Staff commited on Aug 11, 2021

Commit History

Create README.md 304967f

fix config.json c12d373

add final logs 2c4c5b3

final model fc85f04

step 800000 c2346ec

step 750000 dbf35da

step 700000 52d9a48

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step 200000 3f342b5

step 150000 6faf093

step 100000 7add693

step 50000 d787f60

add mistral changes ea70f93

Create codeparrot_training.py 47731b7

Create requirements.txt 6554e3d

add model 05ab0fb

add tokenizer 1c284ad

initial commit f136faa

Create README.md

304967f

fix config.json

c12d373

add final logs

2c4c5b3

final model

fc85f04

step 800000

c2346ec

step 750000

dbf35da

step 700000

52d9a48

step 650000

8da8f1b

step 600000

b49b823

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aa2a5f5

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0c75228

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620eef3

step 200000

3f342b5

step 150000

6faf093

step 100000

7add693

step 50000

d787f60

add mistral changes

ea70f93

Create codeparrot_training.py

47731b7

Create requirements.txt

6554e3d

add model

05ab0fb

add tokenizer

1c284ad

initial commit

f136faa