| --- |
| license: apache-2.0 |
| --- |
| |
| Here is a code to create this tiny model: |
|
|
| ```python |
| import os |
| import torch |
| torch.set_default_dtype(torch.bfloat16) |
| from transformers import AutoTokenizer, AutoConfig, Cohere2ForCausalLM, AutoModelForCausalLM |
| |
| model_id = "CohereLabs/tiny-aya-base" |
| config = AutoConfig.from_pretrained(model_id) |
| |
| config.num_hidden_layers=2 |
| config.layer_types=[ |
| "sliding_attention", |
| "full_attention", |
| ] |
| config.num_attention_heads=4 |
| config.hidden_size=4 |
| config.intermediate_size=5 |
| |
| model = Cohere2ForCausalLM(config) |
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| |
| output_dir = "./tiny-random-aya-base/" |
| os.makedirs(output_dir, exist_ok=True) |
| model.save_pretrained(output_dir, safe_serialization=True) |
| tokenizer.save_pretrained(output_dir) |
| ``` |
|
|