Instructions to use heegyu/ajoublue-gpt2-base-24L with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use heegyu/ajoublue-gpt2-base-24L with Transformers:

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

pipe = pipeline("text-generation", model="heegyu/ajoublue-gpt2-base-24L")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("heegyu/ajoublue-gpt2-base-24L")
model = AutoModelForCausalLM.from_pretrained("heegyu/ajoublue-gpt2-base-24L")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use heegyu/ajoublue-gpt2-base-24L with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "heegyu/ajoublue-gpt2-base-24L"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "heegyu/ajoublue-gpt2-base-24L",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/heegyu/ajoublue-gpt2-base-24L

SGLang

How to use heegyu/ajoublue-gpt2-base-24L 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 "heegyu/ajoublue-gpt2-base-24L" \
    --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": "heegyu/ajoublue-gpt2-base-24L",
		"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 "heegyu/ajoublue-gpt2-base-24L" \
        --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": "heegyu/ajoublue-gpt2-base-24L",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use heegyu/ajoublue-gpt2-base-24L with Docker Model Runner:
```
docker model run hf.co/heegyu/ajoublue-gpt2-base-24L
```

heegyu commited on Feb 7, 2023

Commit

77e216b

1 Parent(s): e8554f2

add pytorch model

Browse files

Files changed (3) hide show

config.json +2 -1
generation_config.json +6 -0
pytorch_model.bin +3 -0

config.json CHANGED Viewed

@@ -32,7 +32,8 @@
       "max_length": 50
     }
   },
-  "transformers_version": "4.25.1",
   "use_cache": true,
   "vocab_size": 51200
 }

       "max_length": 50
     }
   },
+  "torch_dtype": "float32",
+  "transformers_version": "4.26.0",
   "use_cache": true,
   "vocab_size": 51200
 }

generation_config.json ADDED Viewed

	@@ -0,0 +1,6 @@

+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.26.0"
+}

pytorch_model.bin ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:5347a7734a42e6077b97190aa5d14bf3ad56f2bd79b695f398330725c4531b53
+size 866145949