Instructions to use himanshu-dutta/pycoder-gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use himanshu-dutta/pycoder-gpt2 with Transformers:

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

pipe = pipeline("text-generation", model="himanshu-dutta/pycoder-gpt2")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("himanshu-dutta/pycoder-gpt2")
model = AutoModelForCausalLM.from_pretrained("himanshu-dutta/pycoder-gpt2", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use himanshu-dutta/pycoder-gpt2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "himanshu-dutta/pycoder-gpt2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "himanshu-dutta/pycoder-gpt2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/himanshu-dutta/pycoder-gpt2

SGLang

How to use himanshu-dutta/pycoder-gpt2 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 "himanshu-dutta/pycoder-gpt2" \
    --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": "himanshu-dutta/pycoder-gpt2",
		"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 "himanshu-dutta/pycoder-gpt2" \
        --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": "himanshu-dutta/pycoder-gpt2",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use himanshu-dutta/pycoder-gpt2 with Docker Model Runner:
```
docker model run hf.co/himanshu-dutta/pycoder-gpt2
```

himanshu-dutta commited on May 23, 2021

Commit

c254eaf

1 Parent(s): bbedae3

bumped the model to 10 epoch trained version

Browse files

Files changed (4) hide show

README.md +4 -0
added_tokens.json +1 -1
config.json +1 -1
pytorch_model.bin +1 -1

README.md CHANGED Viewed

@@ -8,6 +8,10 @@
 <img alt="Medium" src="https://img.shields.io/badge/Medium-12100E?style=for-the-badge&logo=medium&logoColor=white" height=28 style="display:inline; height:28px;"/>
 [![PyPI version fury.io](https://badge.fury.io/py/pycoder.svg)](https://pypi.org/project/pycoder/)
 </div>

 <img alt="Medium" src="https://img.shields.io/badge/Medium-12100E?style=for-the-badge&logo=medium&logoColor=white" height=28 style="display:inline; height:28px;"/>
+<a href="https://wandb.ai/himanshu-dutta/pycoder">
+<img alt="WandB Dashboard" src="https://raw.githubusercontent.com/wandb/assets/04cfa58cc59fb7807e0423187a18db0c7430bab5/wandb-github-badge-28.svg" height=28 style="display:inline; height:28px;" />
+</a>
 [![PyPI version fury.io](https://badge.fury.io/py/pycoder.svg)](https://pypi.org/project/pycoder/)
 </div>

added_tokens.json CHANGED Viewed

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config.json CHANGED Viewed

@@ -35,7 +35,7 @@
       "max_length": 50
     }
   },
-  "transformers_version": "4.6.0",
   "use_cache": true,
   "vocab_size": 50262
 }

       "max_length": 50
     }
   },
+  "transformers_version": "4.6.1",
   "use_cache": true,
   "vocab_size": 50262
 }

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