Instructions to use Shuu12121/CodeEncoderDecoderModel-Ghost-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Shuu12121/CodeEncoderDecoderModel-Ghost-large with Transformers:

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

pipe = pipeline("text-generation", model="Shuu12121/CodeEncoderDecoderModel-Ghost-large")

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Shuu12121/CodeEncoderDecoderModel-Ghost-large")
model = AutoModelForSeq2SeqLM.from_pretrained("Shuu12121/CodeEncoderDecoderModel-Ghost-large")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Shuu12121/CodeEncoderDecoderModel-Ghost-large with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Shuu12121/CodeEncoderDecoderModel-Ghost-large"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Shuu12121/CodeEncoderDecoderModel-Ghost-large",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Shuu12121/CodeEncoderDecoderModel-Ghost-large

SGLang

How to use Shuu12121/CodeEncoderDecoderModel-Ghost-large 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 "Shuu12121/CodeEncoderDecoderModel-Ghost-large" \
    --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": "Shuu12121/CodeEncoderDecoderModel-Ghost-large",
		"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 "Shuu12121/CodeEncoderDecoderModel-Ghost-large" \
        --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": "Shuu12121/CodeEncoderDecoderModel-Ghost-large",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Shuu12121/CodeEncoderDecoderModel-Ghost-large with Docker Model Runner:
```
docker model run hf.co/Shuu12121/CodeEncoderDecoderModel-Ghost-large
```

Shuu12121 commited on Mar 9

Commit

4cd8a5c

verified ·

1 Parent(s): e5d2aed

Update README.md

Browse files

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README.md +4 -5

README.md CHANGED Viewed

@@ -16,9 +16,9 @@ tags:
 - modernbert
 - gpt2
 base_model:
-  - Shuu12121/CodeModernBERT-Ghost
-  - openai-community/gpt2-large
-pipeline_tag: text2text-generation
 ---
 #　CodeEncoderDecoderModel-Ghost-large👻
@@ -98,5 +98,4 @@ print(docstring)
 ## 📄 License
 Apache-2.0
-Model weights and tokenizer artifacts are released under the same license. You are free to use, modify, and redistribute with attribution.

 - modernbert
 - gpt2
 base_model:
+- Shuu12121/CodeModernBERT-Ghost
+- openai-community/gpt2-large
+pipeline_tag: text-generation
 ---
 #　CodeEncoderDecoderModel-Ghost-large👻
 ## 📄 License
 Apache-2.0
+Model weights and tokenizer artifacts are released under the same license. You are free to use, modify, and redistribute with attribution.