Instructions to use ethannhzhouu/EthanHorror7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ethannhzhouu/EthanHorror7 with Transformers:

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

pipe = pipeline("text-generation", model="ethannhzhouu/EthanHorror7")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ethannhzhouu/EthanHorror7")
model = AutoModelForCausalLM.from_pretrained("ethannhzhouu/EthanHorror7", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ethannhzhouu/EthanHorror7 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ethannhzhouu/EthanHorror7"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ethannhzhouu/EthanHorror7",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ethannhzhouu/EthanHorror7

SGLang

How to use ethannhzhouu/EthanHorror7 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 "ethannhzhouu/EthanHorror7" \
    --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": "ethannhzhouu/EthanHorror7",
		"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 "ethannhzhouu/EthanHorror7" \
        --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": "ethannhzhouu/EthanHorror7",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ethannhzhouu/EthanHorror7 with Docker Model Runner:
```
docker model run hf.co/ethannhzhouu/EthanHorror7
```

EthanHorror7

This model is a fine-tuned version of EleutherAI/gpt-neo-125M on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0296

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	1	2.3768
No log	2.0	2	1.9620
No log	3.0	3	1.7432
No log	4.0	4	1.5631
No log	5.0	5	1.4120
No log	6.0	6	1.2940
No log	7.0	7	1.1950
No log	8.0	8	1.1147
No log	9.0	9	1.0586
No log	10.0	10	1.0296

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

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