Instructions to use AlgorithmicResearchGroup/gpt2-xs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AlgorithmicResearchGroup/gpt2-xs with Transformers:

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

pipe = pipeline("text-generation", model="AlgorithmicResearchGroup/gpt2-xs", device_map="auto")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AlgorithmicResearchGroup/gpt2-xs")
model = AutoModelForCausalLM.from_pretrained("AlgorithmicResearchGroup/gpt2-xs", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AlgorithmicResearchGroup/gpt2-xs with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/AlgorithmicResearchGroup/gpt2-xs

SGLang

How to use AlgorithmicResearchGroup/gpt2-xs 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 "AlgorithmicResearchGroup/gpt2-xs" \
    --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": "AlgorithmicResearchGroup/gpt2-xs",
		"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 "AlgorithmicResearchGroup/gpt2-xs" \
        --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": "AlgorithmicResearchGroup/gpt2-xs",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use AlgorithmicResearchGroup/gpt2-xs with Docker Model Runner:
```
docker model run hf.co/AlgorithmicResearchGroup/gpt2-xs
```

matthewkenney commited on May 2, 2024

Commit

7b4f6aa

verified ·

1 Parent(s): 822993c

Upload folder using huggingface_hub

Browse files

Files changed (2) hide show

config.json +1 -2
model.onnx +3 -0

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/content/2_vsmall_256_epoch_1e_3/checkpoint-5000",
   "activation_function": "gelu_new",
   "architectures": [
     "GPT2LMHeadModel"
@@ -26,7 +26,6 @@
   "summary_proj_to_labels": true,
   "summary_type": "cls_index",
   "summary_use_proj": true,
-  "torch_dtype": "float32",
   "transformers_version": "4.40.1",
   "use_cache": true,
   "vocab_size": 50257

 {
+  "_name_or_path": "ArtifactAI/agent_test_model",
   "activation_function": "gelu_new",
   "architectures": [
     "GPT2LMHeadModel"
   "summary_proj_to_labels": true,
   "summary_type": "cls_index",
   "summary_use_proj": true,
   "transformers_version": "4.40.1",
   "use_cache": true,
   "vocab_size": 50257

model.onnx ADDED Viewed

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

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