Instructions to use ZyanLeyy/gpt2-psych_chatbot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ZyanLeyy/gpt2-psych_chatbot with Transformers:

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

pipe = pipeline("text-generation", model="ZyanLeyy/gpt2-psych_chatbot")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ZyanLeyy/gpt2-psych_chatbot")
model = AutoModelForCausalLM.from_pretrained("ZyanLeyy/gpt2-psych_chatbot")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ZyanLeyy/gpt2-psych_chatbot with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/ZyanLeyy/gpt2-psych_chatbot

SGLang

How to use ZyanLeyy/gpt2-psych_chatbot 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 "ZyanLeyy/gpt2-psych_chatbot" \
    --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": "ZyanLeyy/gpt2-psych_chatbot",
		"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 "ZyanLeyy/gpt2-psych_chatbot" \
        --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": "ZyanLeyy/gpt2-psych_chatbot",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ZyanLeyy/gpt2-psych_chatbot with Docker Model Runner:
```
docker model run hf.co/ZyanLeyy/gpt2-psych_chatbot
```

gpt2-psych_chatbot

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

Loss: 1.9593

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: 0.0002
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: 20

Training results

Training Loss	Epoch	Step	Validation Loss
5.8353	1.0	651	4.8999
4.8713	2.0	1302	4.4407
4.4876	3.0	1953	4.0638
3.7647	4.0	2604	3.7308
3.3969	5.0	3255	3.4360
3.1115	6.0	3906	3.1895
2.4283	7.0	4557	2.9595
2.0813	8.0	5208	2.7442
1.7785	9.0	5859	2.5330
1.3337	10.0	6510	2.3619
1.066	11.0	7161	2.2079
0.9607	12.0	7812	2.1072
0.8078	13.0	8463	2.0385
0.6072	14.0	9114	1.9966
0.5351	15.0	9765	1.9736
0.5049	16.0	10416	1.9646
0.3958	17.0	11067	1.9607
0.346	18.0	11718	1.9592
0.3244	19.0	12369	1.9565
0.2777	20.0	13020	1.9593

Framework versions

Transformers 4.40.2
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Downloads last month: 1

Safetensors

Model size

0.1B params

Tensor type

F32

Model tree for ZyanLeyy/gpt2-psych_chatbot

Base model

openai-community/gpt2

Finetuned

(2173)

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