Instructions to use DeathReaper0965/gpt2-large-code-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DeathReaper0965/gpt2-large-code-generator with Transformers:

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

pipe = pipeline("text-generation", model="DeathReaper0965/gpt2-large-code-generator")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("DeathReaper0965/gpt2-large-code-generator")
model = AutoModelForCausalLM.from_pretrained("DeathReaper0965/gpt2-large-code-generator")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DeathReaper0965/gpt2-large-code-generator with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DeathReaper0965/gpt2-large-code-generator"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DeathReaper0965/gpt2-large-code-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DeathReaper0965/gpt2-large-code-generator

SGLang

How to use DeathReaper0965/gpt2-large-code-generator 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 "DeathReaper0965/gpt2-large-code-generator" \
    --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": "DeathReaper0965/gpt2-large-code-generator",
		"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 "DeathReaper0965/gpt2-large-code-generator" \
        --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": "DeathReaper0965/gpt2-large-code-generator",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DeathReaper0965/gpt2-large-code-generator with Docker Model Runner:
```
docker model run hf.co/DeathReaper0965/gpt2-large-code-generator
```

DeathReaper0965 commited on Aug 28, 2023

Commit

2b8d4c2

1 Parent(s): 6507db9

Update README.md

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README.md +3 -4

README.md CHANGED Viewed

@@ -7,16 +7,15 @@ tags:
 - code-generation
 - gpt2-large
 widget:
-- text: >-
-    def add(a, b):
   example_title: Example 1
-- text: >-
-    def get_files_size(filename):
   example_title: Example 2
 inference:
   parameters:
     max_new_tokens: 30
     num_return_sequences: 1
 ---
 # Code Generation using GPT2-Large

 - code-generation
 - gpt2-large
 widget:
+- text: 'def add(a, b):'
   example_title: Example 1
+- text: 'def get_files_size(filename):'
   example_title: Example 2
 inference:
   parameters:
     max_new_tokens: 30
     num_return_sequences: 1
+pipeline_tag: text-generation
 ---
 # Code Generation using GPT2-Large