Instructions to use jtatman/gpt2-open-instruct-v1-gsm8k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jtatman/gpt2-open-instruct-v1-gsm8k with Transformers:

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

pipe = pipeline("text-generation", model="jtatman/gpt2-open-instruct-v1-gsm8k")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jtatman/gpt2-open-instruct-v1-gsm8k")
model = AutoModelForCausalLM.from_pretrained("jtatman/gpt2-open-instruct-v1-gsm8k", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jtatman/gpt2-open-instruct-v1-gsm8k with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jtatman/gpt2-open-instruct-v1-gsm8k"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jtatman/gpt2-open-instruct-v1-gsm8k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/jtatman/gpt2-open-instruct-v1-gsm8k

SGLang

How to use jtatman/gpt2-open-instruct-v1-gsm8k 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 "jtatman/gpt2-open-instruct-v1-gsm8k" \
    --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": "jtatman/gpt2-open-instruct-v1-gsm8k",
		"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 "jtatman/gpt2-open-instruct-v1-gsm8k" \
        --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": "jtatman/gpt2-open-instruct-v1-gsm8k",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use jtatman/gpt2-open-instruct-v1-gsm8k with Docker Model Runner:
```
docker model run hf.co/jtatman/gpt2-open-instruct-v1-gsm8k
```

gpt2-open-instruct-v1-gsm8k

This model is a fine-tuned version of vicgalle/gpt2-open-instruct-v1 on the gsm8k dataset. It achieves the following results on the evaluation set:

Loss: 2.3966

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: 0.0005
train_batch_size: 16
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	468	2.5579
2.859	2.0	936	2.5018
2.6455	3.0	1404	2.4752
2.6025	4.0	1872	2.4590
2.5777	5.0	2340	2.4473
2.5557	6.0	2808	2.4388
2.538	7.0	3276	2.4309
2.5246	8.0	3744	2.4236
2.514	9.0	4212	2.4186
2.5059	10.0	4680	2.4159
2.4944	11.0	5148	2.4107
2.4874	12.0	5616	2.4078
2.4862	13.0	6084	2.4053
2.475	14.0	6552	2.4027
2.4716	15.0	7020	2.4008
2.4716	16.0	7488	2.3995
2.4704	17.0	7956	2.3985
2.4648	18.0	8424	2.3973
2.4634	19.0	8892	2.3968
2.459	20.0	9360	2.3966

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Downloads last month: 17

Model tree for jtatman/gpt2-open-instruct-v1-gsm8k

Base model

vicgalle/gpt2-open-instruct-v1

Finetuned

(3)

this model

jtatman
/

gpt2-open-instruct-v1-gsm8k

gpt2-open-instruct-v1-gsm8k

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Model tree for jtatman/gpt2-open-instruct-v1-gsm8k

Dataset used to train jtatman/gpt2-open-instruct-v1-gsm8k