Instructions to use Davlan/m2m100_418M-yor-eng-mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Davlan/m2m100_418M-yor-eng-mt with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Davlan/m2m100_418M-yor-eng-mt") model = AutoModelForSeq2SeqLM.from_pretrained("Davlan/m2m100_418M-yor-eng-mt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Davlan/m2m100_418M-yor-eng-mt: direct link, hf CLI and curl.
- Browser
- Download file 964 Bytes
-
https://huggingface.co/Davlan/m2m100_418M-yor-eng-mt/resolve/main/config.json
- Command line
-
hf download hf://Davlan/m2m100_418M-yor-eng-mt/config.json
-
curl -L -o config.json https://huggingface.co/Davlan/m2m100_418M-yor-eng-mt/resolve/main/config.json
964 Bytes
| { | |
| "_name_or_path": "facebook/m2m100_418M", | |
| "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": 0.05, | |
| "decoder_layers": 12, | |
| "decoder_start_token_id": 2, | |
| "dropout": 0.1, | |
| "early_stopping": true, | |
| "encoder_attention_heads": 16, | |
| "encoder_ffn_dim": 4096, | |
| "encoder_layerdrop": 0.05, | |
| "encoder_layers": 12, | |
| "eos_token_id": 2, | |
| "forced_bos_token_id": 128022, | |
| "gradient_checkpointing": false, | |
| "init_std": 0.02, | |
| "is_encoder_decoder": true, | |
| "max_length": 200, | |
| "max_position_embeddings": 1024, | |
| "model_type": "m2m_100", | |
| "num_beams": 5, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 1, | |
| "scale_embedding": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.10.3", | |
| "use_cache": true, | |
| "vocab_size": 128112 | |
| } | |