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

Libraries

How to use flax-community/gpt2-bengali with Transformers:

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

pipe = pipeline("text-generation", model="flax-community/gpt2-bengali")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("flax-community/gpt2-bengali")
model = AutoModelForCausalLM.from_pretrained("flax-community/gpt2-bengali")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use flax-community/gpt2-bengali with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/flax-community/gpt2-bengali

SGLang

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

Docker Model Runner
How to use flax-community/gpt2-bengali with Docker Model Runner:
```
docker model run hf.co/flax-community/gpt2-bengali
```

Bengali GPT-2

Bengali GPT-2 demo. Part of the Huggingface JAX/Flax event. Also features a finetuned model on bengali song lyrics.

Model Description

OpenAI GPT-2 model was proposed in Language Models are Unsupervised Multitask Learners paper .Original GPT2 model was a causal (unidirectional) transformer pretrained using language modeling on a very large corpus of ~40 GB of text data. This model has same configuration but has been pretrained on bengali corpus of mC4(multilingual C4) dataset. The code for training the model has all been open-sourced here.

Training Details

Overall Result:

Eval loss : 1.45, Eval Perplexity : 3.141

Data: mC4-bn

Train Steps: 250k steps

link 🤗 flax-community/gpt2-bengali

Demo : https://huggingface.co/spaces/flax-community/Gpt2-bengali

Usage

For using the model there are multiple options available. For example using the pipeline directly we can try to generate sentences.

from transformers import pipeline

gpt2_bengali = pipeline('text-generation',model="flax-community/gpt2-bengali", tokenizer='flax-community/gpt2-bengali')

Similarly for using the finetuned model on bangla songs we can use following.

from transformers import pipeline

singer = pipeline('text-generation',model="khalidsaifullaah/bengali-lyricist-gpt2", tokenizer='khalidsaifullaah/bengali-lyricist-gpt2')

For using on other tasks the model needs to be fine-tuned on custom datasets. Details can be found in huggingface documentation

Contributors

Khalid Saifullah
Tasmiah Tahsin Mayeesha
Ritobrata Ghosh
Ibrahim Musa
M Saiful Bari

BibTeX entry and citation info

@misc {flax_community_2023, author = { {Flax Community} }, title = { gpt2-bengali (Revision cb8fff6) }, year = 2023, url = { https://huggingface.co/flax-community/gpt2-bengali }, doi = { 10.57967/hf/0938 }, publisher = { Hugging Face } }

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Safetensors

Model size

0.1B params

Tensor type

F32

flax-community
/

gpt2-bengali