Instructions to use susnato/codeparrot-small2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use susnato/codeparrot-small2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="susnato/codeparrot-small2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("susnato/codeparrot-small2") model = AutoModelForCausalLM.from_pretrained("susnato/codeparrot-small2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use susnato/codeparrot-small2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "susnato/codeparrot-small2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "susnato/codeparrot-small2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/susnato/codeparrot-small2
- SGLang
How to use susnato/codeparrot-small2 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 "susnato/codeparrot-small2" \ --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": "susnato/codeparrot-small2", "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 "susnato/codeparrot-small2" \ --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": "susnato/codeparrot-small2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use susnato/codeparrot-small2 with Docker Model Runner:
docker model run hf.co/susnato/codeparrot-small2
Commit History
-
Trained for Epoch - 16
9a8d73f -
Trained for Epoch - 16 save_checkpoint_steps reached!
eabb270 -
Trained for Epoch - 16 save_checkpoint_steps reached!
2a28a81 -
Trained for Epoch - 16 save_checkpoint_steps reached!
15e368b -
Trained for Epoch - 16 save_checkpoint_steps reached!
6b3a3ce -
Trained for Epoch - 16 save_checkpoint_steps reached!
3c587d8 -
Trained for Epoch - 15
3de7e8f -
Trained for Epoch - 15 save_checkpoint_steps reached!
9981e35 -
Trained for Epoch - 15 save_checkpoint_steps reached!
3abdb87 -
Trained for Epoch - 15 save_checkpoint_steps reached!
18d2ab7 -
Trained for Epoch - 15 save_checkpoint_steps reached!
21499ee -
Trained for Epoch - 15 save_checkpoint_steps reached!
e458dcc -
Trained for Epoch - 14
fc82f52 -
Trained for Epoch - 14 save_checkpoint_steps reached!
069ecb0 -
Trained for Epoch - 14 save_checkpoint_steps reached!
61f1bc9 -
Trained for Epoch - 14 save_checkpoint_steps reached!
52f56bf -
Trained for Epoch - 14 save_checkpoint_steps reached!
a7357ac -
Trained for Epoch - 14 save_checkpoint_steps reached!
9e48b1e -
Trained for Epoch - 13
3eb6bed -
Trained for Epoch - 13 save_checkpoint_steps reached!
f4bccb3 -
Trained for Epoch - 13 save_checkpoint_steps reached!
bccce03 -
Trained for Epoch - 13 save_checkpoint_steps reached!
fb95a62 -
Trained for Epoch - 13 save_checkpoint_steps reached!
7d8cf5f -
Trained for Epoch - 13 save_checkpoint_steps reached!
faae084 -
Trained for Epoch - 12
d943c11 -
Trained for Epoch - 12 save_checkpoint_steps reached!
fbab0bf -
Trained for Epoch - 12 save_checkpoint_steps reached!
72600d4 -
Trained for Epoch - 12 save_checkpoint_steps reached!
51a6b7e -
Trained for Epoch - 12 save_checkpoint_steps reached!
6feffd0 -
Trained for Epoch - 12 save_checkpoint_steps reached!
7a412f1 -
Trained for Epoch - 12 save_checkpoint_steps reached!
bed158e -
Trained for Epoch - 12 save_checkpoint_steps reached!
e1836bd -
Trained for Epoch - 12 save_checkpoint_steps reached!
9c87bd7 -
Trained for Epoch - 12 save_checkpoint_steps reached!
c1736bb -
Trained for Epoch - 12 save_checkpoint_steps reached!
ee58a33 -
Trained for Epoch - 12 save_checkpoint_steps reached!
61e095f -
Trained for Epoch - 12 save_checkpoint_steps reached!
a9579f4 -
Trained for Epoch - 12 save_checkpoint_steps reached!
27f57f8 -
Trained for Epoch - 12 save_checkpoint_steps reached!
b0ed4b5 -
Trained for Epoch - 12 save_checkpoint_steps reached!
5f91f76 -
Trained for Epoch - 12 save_checkpoint_steps reached!
b32e29f -
Trained for Epoch - 12 save_checkpoint_steps reached!
1cb119e -
Trained for Epoch - 12 save_checkpoint_steps reached!
c705a37 -
Trained for Epoch - 12 save_checkpoint_steps reached!
c9ad8f8 -
Trained for Epoch - 12 save_checkpoint_steps reached!
7888a84 -
Trained for Epoch - 12 save_checkpoint_steps reached!
e3879f7 -
Trained for Epoch - 12 save_checkpoint_steps reached!
59be7b9 -
Trained for Epoch - 12 save_checkpoint_steps reached!
f944da2 -
Trained for Epoch - 12 save_checkpoint_steps reached!
0fd46e4 -
Trained for Epoch - 12 save_checkpoint_steps reached!
133c179