How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "not-lain/PyGPT"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "not-lain/PyGPT",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/not-lain/PyGPT
Quick Links

Model Details

this is the finetuned version of GPT2 on a coding dataset

Model Description

  • Model type: text-generation
  • Finetuned from model GPT2

Model Sources

Uses

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

pipe = pipeline("text-generation", model="not-lain/PyGPT")
prompt = """
Below is an instruction that describes a task. Write a response that
appropriately completes the request.


### Instruction:

Create a function to calculate the sum of a sequence of integers.


### Input:

[1, 2, 3, 4, 5]


### Output:
"""

pipe(prompt)

Bias, Risks, and Limitations

model may produce biased ,erroneous and output.

Recommendations

it is not advised to use this model as it is just a product of testing a finetuning script

Training Details

Training Data

[More Information Needed]

Evaluation

please refer to the tensorboard tab for full details

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Dataset used to train not-lain/PyGPT

Space using not-lain/PyGPT 1