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1ct2-transformers-converter \
2 --model facebook/nllb-200-distilled-600M \
3 --output_dir nllb-600m-ct2 \
4 --quantization int81import ctranslate2
2from transformers import AutoTokenizer
3from huggingface_hub import snapshot_download
4
5REPO_ID = "pulkitchowdry/nllb-600m-ct2-int8"
6
7# Download model from Hugging Face
8model_dir = snapshot_download(repo_id=REPO_ID)
9
10print("Model downloaded to:", model_dir)
11
12# Load translator
13translator = ctranslate2.Translator(
14 model_dir,
15 device="cpu"
16)
17
18# Load tokenizer
19tokenizer = AutoTokenizer.from_pretrained(model_dir, fix_mistral_regex=True)
20
21src_lang = "eng_Latn"
22tgt_lang = "fra_Latn"
23
24text = "Hello, how are you today?"
25
26tokenizer.src_lang = src_lang
27
28# Tokenize
29input_ids = tokenizer(text).input_ids
30tokens = tokenizer.convert_ids_to_tokens(input_ids)
31
32# Translate
33results = translator.translate_batch(
34 [tokens],
35 target_prefix=[[tgt_lang]]
36)
37
38output_tokens = results[0].hypotheses[0]
39
40translation = tokenizer.decode(
41 tokenizer.convert_tokens_to_ids(output_tokens),
42 skip_special_tokens=True,
43)
44
45print("Input:", text)
46print("Translation:", translation)
47