Instructions to use betteib/gp2_basemodel_v13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use betteib/gp2_basemodel_v13 with Transformers:

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

pipe = pipeline("text-generation", model="betteib/gp2_basemodel_v13")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("betteib/gp2_basemodel_v13")
model = AutoModelForCausalLM.from_pretrained("betteib/gp2_basemodel_v13", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use betteib/gp2_basemodel_v13 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "betteib/gp2_basemodel_v13"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "betteib/gp2_basemodel_v13",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/betteib/gp2_basemodel_v13

SGLang

How to use betteib/gp2_basemodel_v13 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 "betteib/gp2_basemodel_v13" \
    --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": "betteib/gp2_basemodel_v13",
		"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 "betteib/gp2_basemodel_v13" \
        --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": "betteib/gp2_basemodel_v13",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use betteib/gp2_basemodel_v13 with Docker Model Runner:
```
docker model run hf.co/betteib/gp2_basemodel_v13
```

Model Card for Model ID

Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

Developed by: Bacem ETTEIB
Funded by: University of Luxembourg
Model type: Encoder only model
Language(s) (NLP): Tunisian dialect
License: MIT
Finetuned from model: GPT2

Recommendations

Fine tune on different downstream tasks such as sentiment analysis or dialect identitication.

Training Procedure

Continual pretraining.

Downloads last month: 12

Safetensors

Model size

0.1B params

Tensor type

F16

Model tree for betteib/gp2_basemodel_v13

Base model

openai-community/gpt2

Finetuned

(2262)

this model