Instructions to use juni3227/codeparrot-ds with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use juni3227/codeparrot-ds with Transformers:

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

pipe = pipeline("text-generation", model="juni3227/codeparrot-ds")

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

tokenizer = AutoTokenizer.from_pretrained("juni3227/codeparrot-ds")
model = AutoModelForCausalLM.from_pretrained("juni3227/codeparrot-ds", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use juni3227/codeparrot-ds with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "juni3227/codeparrot-ds"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "juni3227/codeparrot-ds",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/juni3227/codeparrot-ds

SGLang

How to use juni3227/codeparrot-ds 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 "juni3227/codeparrot-ds" \
    --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": "juni3227/codeparrot-ds",
		"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 "juni3227/codeparrot-ds" \
        --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": "juni3227/codeparrot-ds",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use juni3227/codeparrot-ds with Docker Model Runner:
```
docker model run hf.co/juni3227/codeparrot-ds
```

juni3227 commited on Oct 14, 2025

Commit

15d024c

verified ·

1 Parent(s): 130fc0e

Training in progress, step 40000

Browse files

Files changed (1) hide show

model.safetensors +1 -1

model.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:ff0bc94449e5b80afc96c903ffc59fb76dc544158f2ba6be529c9f03a6412e0a
 size 496984704

 version https://git-lfs.github.com/spec/v1
+oid sha256:0b5e5cf9a3072f7687b812230fa96a4c47f66651d2faf7e68a403d053116e718
 size 496984704