Instructions to use LouisSanna/orpo-model-output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LouisSanna/orpo-model-output with Transformers:

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

pipe = pipeline("text-generation", model="LouisSanna/orpo-model-output")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("LouisSanna/orpo-model-output")
model = AutoModelForCausalLM.from_pretrained("LouisSanna/orpo-model-output")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use LouisSanna/orpo-model-output with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/LouisSanna/orpo-model-output

SGLang

How to use LouisSanna/orpo-model-output 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 "LouisSanna/orpo-model-output" \
    --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": "LouisSanna/orpo-model-output",
		"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 "LouisSanna/orpo-model-output" \
        --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": "LouisSanna/orpo-model-output",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use LouisSanna/orpo-model-output with Docker Model Runner:
```
docker model run hf.co/LouisSanna/orpo-model-output
```

orpo-model-output

This model is a fine-tuned version of openai-community/gpt2 on the piqa dataset. It achieves the following results on the evaluation set:

Loss: 3.2999
Rewards/chosen: -0.3182
Rewards/rejected: -0.3369
Rewards/accuracies: 0.6693
Rewards/margins: 0.0187
Logps/rejected: -3.3688
Logps/chosen: -3.1821
Logits/rejected: -24.5739
Logits/chosen: -24.6603
Nll Loss: 3.2330
Log Odds Ratio: -0.6695
Log Odds Chosen: 0.2013

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen	Nll Loss	Log Odds Ratio	Log Odds Chosen
3.1799	1.0	3223	3.1575	-0.2992	-0.3103	0.6472	0.0111	-3.1030	-2.9917	-16.2781	-16.3180	3.0900	-0.6758	0.1201
2.7077	2.0	6446	3.1544	-0.3005	-0.3160	0.6652	0.0154	-3.1595	-3.0051	-21.7517	-21.8387	3.0878	-0.6671	0.1676
2.2691	3.0	9669	3.2999	-0.3182	-0.3369	0.6693	0.0187	-3.3688	-3.1821	-24.5739	-24.6603	3.2330	-0.6695	0.2013

Framework versions

Transformers 4.44.2
Pytorch 2.0.0
Datasets 2.16.1
Tokenizers 0.19.1

Downloads last month: 2

Safetensors

Model size

0.1B params

Tensor type

F32

Model tree for LouisSanna/orpo-model-output

Base model

openai-community/gpt2

Finetuned

(2160)

this model

LouisSanna
/

orpo-model-output

orpo-model-output

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Model tree for LouisSanna/orpo-model-output

Dataset used to train LouisSanna/orpo-model-output