Text Generation
Transformers
Safetensors
PEFT
Burmese
m2m_100
text2text-generation
burmese
myanmar
myanmar-language
burmese-nlp
style-transfer
text-rewriting
formal-to-informal
written-to-spoken
seq2seq
nllb
lora
low-resource-language
Eval Results (legacy)
Instructions to use DatarrX/myX-TransStyle-W2S with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DatarrX/myX-TransStyle-W2S with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DatarrX/myX-TransStyle-W2S")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("DatarrX/myX-TransStyle-W2S") model = AutoModelForMultimodalLM.from_pretrained("DatarrX/myX-TransStyle-W2S") - PEFT
How to use DatarrX/myX-TransStyle-W2S with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DatarrX/myX-TransStyle-W2S with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DatarrX/myX-TransStyle-W2S" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DatarrX/myX-TransStyle-W2S", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DatarrX/myX-TransStyle-W2S
- SGLang
How to use DatarrX/myX-TransStyle-W2S 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 "DatarrX/myX-TransStyle-W2S" \ --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": "DatarrX/myX-TransStyle-W2S", "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 "DatarrX/myX-TransStyle-W2S" \ --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": "DatarrX/myX-TransStyle-W2S", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DatarrX/myX-TransStyle-W2S with Docker Model Runner:
docker model run hf.co/DatarrX/myX-TransStyle-W2S
| { | |
| "activation_dropout": 0.0, | |
| "activation_function": "relu", | |
| "architectures": [ | |
| "M2M100ForConditionalGeneration" | |
| ], | |
| "attention_dropout": 0.1, | |
| "bos_token_id": 0, | |
| "d_model": 1024, | |
| "decoder_attention_heads": 16, | |
| "decoder_ffn_dim": 4096, | |
| "decoder_layerdrop": 0, | |
| "decoder_layers": 12, | |
| "decoder_start_token_id": 2, | |
| "dropout": 0.1, | |
| "dtype": "float16", | |
| "encoder_attention_heads": 16, | |
| "encoder_ffn_dim": 4096, | |
| "encoder_layerdrop": 0, | |
| "encoder_layers": 12, | |
| "eos_token_id": 2, | |
| "init_std": 0.02, | |
| "is_encoder_decoder": true, | |
| "max_position_embeddings": 1024, | |
| "model_type": "m2m_100", | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "scale_embedding": true, | |
| "tie_word_embeddings": true, | |
| "tokenizer_class": "NllbTokenizer", | |
| "transformers_version": "5.0.0", | |
| "use_cache": true, | |
| "vocab_size": 256206 | |
| } | |