Instructions to use Rahulrr/language_model_en_de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rahulrr/language_model_en_de 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="Rahulrr/language_model_en_de")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Rahulrr/language_model_en_de") model = AutoModelForSeq2SeqLM.from_pretrained("Rahulrr/language_model_en_de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download metadata.json from Rahulrr/language_model_en_de: direct link, hf CLI and curl.
- Browser
- Download file 1.1 kB
-
https://huggingface.co/Rahulrr/language_model_en_de/resolve/main/metadata.json
- Command line
-
hf download hf://Rahulrr/language_model_en_de/metadata.json
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curl -L -o metadata.json https://huggingface.co/Rahulrr/language_model_en_de/resolve/main/metadata.json
1.1 kB
| {"hf_name":"en-de","source_languages":"eng","target_languages":"deu","opus_readme_url":"https:\/\/github.com\/Helsinki-NLP\/Tatoeba-Challenge\/tree\/master\/models\/eng-deu\/README.md","original_repo":"Tatoeba-Challenge","tags":["translation"],"languages":["en","de"],"src_constituents":["English",["eng"]],"tgt_constituents":["German",["deu"]],"src_multilingual":false,"tgt_multilingual":false,"long_pair":"eng-deu","prepro":" normalization + SentencePiece (spm32k,spm32k)","url_model":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/eng-deu\/opusTCv20210807+bt-2021-12-08.zip","url_test_set":"https:\/\/object.pouta.csc.fi\/Tatoeba-MT-models\/eng-deu\/opusTCv20210807+bt-2021-12-08.test.txt","src_alpha3":"eng","tgt_alpha3":"deu","chrF2_score":0.6442,"bleu":43.7,"src_name":"English","tgt_name":"German","train_date":1638921600000,"src_alpha2":"en","tgt_alpha2":"de","prefer_old":false,"short_pair":"en-de","helsinki_git_sha":"c4e978d8de47875b482653b423dcfe968979d7d5","transformers_git_sha":"56b83cf049823ed074a655eceb28f31e2077c6eb","port_machine":"LAPIN4GLQ2G3","port_time":"2022-06-27-16:10"} |