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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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Training Details
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Training Procedure
1
2from transformers import MBart50TokenizerFast, MBartForConditionalGeneration
3import torch
4
5repo_id = "frankmorales2020/kkadian-to-spanish-translator"
6tokenizer = MBart50TokenizerFast.from_pretrained(repo_id)
7model = MBartForConditionalGeneration.from_pretrained(repo_id)
8
9def test_model(sentences):
10 tokenizer.src_lang = "[akk_AK]"
11 es_id = tokenizer.convert_tokens_to_ids("es_XX")
12
13 for text in sentences:
14 inputs = tokenizer(text, return_tensors="pt")
15 with torch.no_grad():
16 generated_tokens = model.generate(
17 **inputs,
18 forced_bos_token_id=es_id,
19 max_new_tokens=60,
20 num_beams=5
21 )
22 translation = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
23
24 print("-" * 40)
25 print(f"AKKADIAN: {text}")
26 print(f"SPANISH: {translation}")
27
28# List your test cases here
29examples = [
30 "šarrum bītam iṣbat",
31 "ekallam īpuš"
32]
33
34test_model(examples)
35print("-" * 40)
1
2----------------------------------------
3AKKADIAN: šarrum bītam iṣbat
4SPANISH: el rey tomó la casa
5----------------------------------------
6AKKADIAN: ekallam īpuš
7SPANISH: él construyó el palacio
8----------------------------------------
9
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Machine Learning Impact calculator presented in
Lacoste et al. (2019).
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