Instructions to use bubai567/rubbish_gpt_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bubai567/rubbish_gpt_test with Transformers:

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

pipe = pipeline("text-generation", model="bubai567/rubbish_gpt_test")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("bubai567/rubbish_gpt_test")
model = AutoModelForCausalLM.from_pretrained("bubai567/rubbish_gpt_test", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use bubai567/rubbish_gpt_test with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bubai567/rubbish_gpt_test"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bubai567/rubbish_gpt_test",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/bubai567/rubbish_gpt_test

SGLang

How to use bubai567/rubbish_gpt_test 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 "bubai567/rubbish_gpt_test" \
    --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": "bubai567/rubbish_gpt_test",
		"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 "bubai567/rubbish_gpt_test" \
        --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": "bubai567/rubbish_gpt_test",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use bubai567/rubbish_gpt_test with Docker Model Runner:
```
docker model run hf.co/bubai567/rubbish_gpt_test
```

bubai567/rubbish_gpt_test

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.5595
Train Accuracy: 0.9435
Epoch: 1

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:

optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': 0.001, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
training_precision: float32

Training results

Train Loss	Train Accuracy	Epoch
1.7043	0.9189	0
0.5595	0.9435	1

Framework versions

Transformers 4.34.1
TensorFlow 2.14.0
Datasets 2.14.6
Tokenizers 0.14.1

Downloads last month: 16

Model tree for bubai567/rubbish_gpt_test

Base model

openai-community/gpt2

Finetuned

(2,353)

this model