Transformers
PyTorch
Safetensors
English
Russian
t5
text2text-generation
Cometrain AutoCode
Cometrain AlphaML
moex
text-generation-inference
Instructions to use cometrain/moexT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cometrain/moexT5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cometrain/moexT5") model = AutoModelForSeq2SeqLM.from_pretrained("cometrain/moexT5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 712 Bytes
913a516 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | {
"_name_or_path": "t5-small",
"architectures": [
"T5ForConditionalGeneration"
],
"d_ff": 2048,
"d_kv": 64,
"d_model": 512,
"decoder_start_token_id": 0,
"dropout_rate": 0.1,
"eos_token_id": 1,
"feed_forward_proj": "relu",
"initializer_factor": 1.0,
"is_encoder_decoder": true,
"layer_norm_epsilon": 1e-06,
"model_type": "t5",
"n_positions": 512,
"num_decoder_layers": 6,
"num_heads": 8,
"num_layers": 6,
"output_past": true,
"pad_token_id": 0,
"relative_attention_max_distance": 128,
"relative_attention_num_buckets": 32,
"task_specific_params": {
},
"torch_dtype": "float32",
"transformers_version": "4.18.0",
"use_cache": true,
"vocab_size": 32128
}
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