Instructions to use shibing624/code-autocomplete-distilgpt2-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use shibing624/code-autocomplete-distilgpt2-python with Transformers:

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

pipe = pipeline("text-generation", model="shibing624/code-autocomplete-distilgpt2-python")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("shibing624/code-autocomplete-distilgpt2-python")
model = AutoModelForCausalLM.from_pretrained("shibing624/code-autocomplete-distilgpt2-python")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use shibing624/code-autocomplete-distilgpt2-python with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "shibing624/code-autocomplete-distilgpt2-python"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "shibing624/code-autocomplete-distilgpt2-python",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/shibing624/code-autocomplete-distilgpt2-python

SGLang

How to use shibing624/code-autocomplete-distilgpt2-python 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 "shibing624/code-autocomplete-distilgpt2-python" \
    --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": "shibing624/code-autocomplete-distilgpt2-python",
		"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 "shibing624/code-autocomplete-distilgpt2-python" \
        --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": "shibing624/code-autocomplete-distilgpt2-python",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use shibing624/code-autocomplete-distilgpt2-python with Docker Model Runner:
```
docker model run hf.co/shibing624/code-autocomplete-distilgpt2-python
```

shibing624 commited on Feb 15, 2022

Commit

0109289

1 Parent(s): 63f9712

Upload tokenizer_config.json

Browse files

Files changed (1) hide show

tokenizer_config.json +1 -0

tokenizer_config.json ADDED Viewed

	@@ -0,0 +1 @@

+ {"errors": "replace", "unk_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "<|endoftext|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "do_lower_case": false, "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "distilgpt2", "tokenizer_class": "GPT2Tokenizer"}