Instructions to use sultan-hassan/tinygpt_arxiv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use sultan-hassan/tinygpt_arxiv with Transformers:

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

pipe = pipeline("text-generation", model="sultan-hassan/tinygpt_arxiv")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("sultan-hassan/tinygpt_arxiv")
model = AutoModelForCausalLM.from_pretrained("sultan-hassan/tinygpt_arxiv")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use sultan-hassan/tinygpt_arxiv with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/sultan-hassan/tinygpt_arxiv

SGLang

How to use sultan-hassan/tinygpt_arxiv 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 "sultan-hassan/tinygpt_arxiv" \
    --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": "sultan-hassan/tinygpt_arxiv",
		"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 "sultan-hassan/tinygpt_arxiv" \
        --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": "sultan-hassan/tinygpt_arxiv",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use sultan-hassan/tinygpt_arxiv with Docker Model Runner:
```
docker model run hf.co/sultan-hassan/tinygpt_arxiv
```

tinygpt_arxiv

This model is trained from scratch using AIGym/TinyGPT2-81M on article abstracts from arxiv. It achieves the following results on the evaluation set:

Loss: 5.4123

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 500
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
3.5186	17.2414	1000	4.0977
0.5985	34.4828	2000	5.4123

Framework versions

Transformers 4.42.4
Pytorch 2.2.2
Datasets 2.20.0
Tokenizers 0.19.1

Downloads last month: 1

Safetensors

Model size

81.2M params

Tensor type

F32