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

Libraries

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

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

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

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

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

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LouisSanna/dpo-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/dpo-model-output",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

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

SGLang

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

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

dpo-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: 1.0022
Rewards/chosen: -17.7008
Rewards/rejected: -19.2025
Rewards/accuracies: 0.6638
Rewards/margins: 1.5016
Logps/rejected: -283.3009
Logps/chosen: -266.5706
Logits/rejected: -79.0250
Logits/chosen: -79.1854

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
0.717	1.0	3223	0.6773	-6.7817	-7.2423	0.6513	0.4606	-163.6990	-157.3790	-76.4738	-76.4513
0.3122	2.0	6446	0.7910	-12.1665	-13.1665	0.6675	1.0000	-222.9408	-211.2272	-85.8639	-85.9837
0.0481	3.0	9669	1.0022	-17.7008	-19.2025	0.6638	1.5016	-283.3009	-266.5706	-79.0250	-79.1854

Framework versions

Transformers 4.44.2
Pytorch 2.0.0
Datasets 2.16.1
Tokenizers 0.19.1

Downloads last month: 3

Safetensors

Model size

0.1B params

Tensor type

F32

Model tree for LouisSanna/dpo-model-output

Base model

openai-community/gpt2

Finetuned

(2160)

this model

LouisSanna
/

dpo-model-output

dpo-model-output

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Model tree for LouisSanna/dpo-model-output

Dataset used to train LouisSanna/dpo-model-output