Instructions to use AMindToThink/ppo_push_main_13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AMindToThink/ppo_push_main_13 with Transformers:

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

pipe = pipeline("text-generation", model="AMindToThink/ppo_push_main_13")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AMindToThink/ppo_push_main_13")
model = AutoModelForCausalLM.from_pretrained("AMindToThink/ppo_push_main_13")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AMindToThink/ppo_push_main_13 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AMindToThink/ppo_push_main_13"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AMindToThink/ppo_push_main_13",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AMindToThink/ppo_push_main_13

SGLang

How to use AMindToThink/ppo_push_main_13 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 "AMindToThink/ppo_push_main_13" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AMindToThink/ppo_push_main_13",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "AMindToThink/ppo_push_main_13" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AMindToThink/ppo_push_main_13",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AMindToThink/ppo_push_main_13 with Docker Model Runner:
```
docker model run hf.co/AMindToThink/ppo_push_main_13
```

AMindToThink commited on Apr 16, 2025

Commit

f41d099

verified ·

1 Parent(s): f334dd1

End of training

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README.md +2 -1

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@@ -1,5 +1,6 @@
 ---
 base_model: EleutherAI/pythia-160m
 library_name: transformers
 model_name: ppo_push_main_13
 tags:
@@ -9,7 +10,7 @@ licence: license
 # Model Card for ppo_push_main_13
-This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m).
 It has been trained using [TRL](https://github.com/huggingface/trl).
 ## Quick start

 ---
 base_model: EleutherAI/pythia-160m
+datasets: trl-internal-testing/descriptiveness-sentiment-trl-style
 library_name: transformers
 model_name: ppo_push_main_13
 tags:
 # Model Card for ppo_push_main_13
+This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) on the [trl-internal-testing/descriptiveness-sentiment-trl-style](https://huggingface.co/datasets/trl-internal-testing/descriptiveness-sentiment-trl-style) dataset.
 It has been trained using [TRL](https://github.com/huggingface/trl).
 ## Quick start