Instructions to use Helsinki-NLP/opus-mt-itc-itc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Helsinki-NLP/opus-mt-itc-itc with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-itc-itc")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-itc-itc") model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-itc-itc") - Notebooks
- Google Colab
- Kaggle
| {"hf_name":"itc-itc","source_languages":"itc","target_languages":"itc","opus_readme_url":"https:\/\/github.com\/Helsinki-NLP\/Tatoeba-Challenge\/tree\/master\/models\/itc-itc\/README.md","original_repo":"Tatoeba-Challenge","tags":["translation"],"languages":["it","ca","rm","es","ro","gl","sc","co","wa","pt","oc","an","id","fr","ht","itc"],"src_constituents":["ita","cat","roh","spa","pap","bjn","lmo","mwl","lij","lat_Latn","lad_Latn","pcd","lat_Grek","ext","ron","ast","glg","pms","zsm_Latn","srd","gcf_Latn","lld_Latn","min","tmw_Latn","cos","wln","zlm_Latn","por","egl","oci","vec","arg","ind","fra","hat","lad","max_Latn","frm_Latn","scn","mfe"],"tgt_constituents":["ita","cat","roh","spa","pap","bjn","lmo","mwl","lij","lat_Latn","lad_Latn","pcd","lat_Grek","ext","ron","ast","glg","pms","zsm_Latn","srd","gcf_Latn","lld_Latn","min","tmw_Latn","cos","wln","zlm_Latn","por","egl","oci","vec","arg","ind","fra","hat","lad","max_Latn","frm_Latn","scn","mfe"],"src_multilingual":true,"tgt_multilingual":true,"prepro":" normalization + SentencePiece (spm32k,spm32k)","url_model":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/itc-itc\/opus-2020-07-07.zip","url_test_set":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/itc-itc\/opus-2020-07-07.test.txt","src_alpha3":"itc","tgt_alpha3":"itc","short_pair":"itc-itc","chrF2_score":0.599,"bleu":40.8,"brevity_penalty":0.968,"ref_len":77448.0,"src_name":"Italic languages","tgt_name":"Italic languages","train_date":"2020-07-07","src_alpha2":"itc","tgt_alpha2":"itc","prefer_old":false,"long_pair":"itc-itc","helsinki_git_sha":"480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535","transformers_git_sha":"2207e5d8cb224e954a7cba69fa4ac2309e9ff30b","port_machine":"brutasse","port_time":"2020-08-21-14:41"} |