| hf_translate | R Documentation |
Translate text from one language to another using a translation model via the Hugging Face Inference Providers API.
hf_translate(
text,
model = hf_default_model("translate"),
source = NULL,
target = NULL,
token = NULL,
endpoint_url = NULL,
...
)
text |
Character vector of text(s) to translate. |
model |
Character string. Model ID from the Hugging Face Hub. Append '":provider"' to select an inference provider. Default: "Helsinki-NLP/opus-mt-en-fr" (English to French). |
source |
Character string or NULL. Source language code (model-specific; ignored by 'opus-mt-*' language-pair models). |
target |
Character string or NULL. Target language code (model-specific; ignored by 'opus-mt-*' language-pair models). |
token |
Character string or NULL. API token for authentication. |
endpoint_url |
Character string or NULL. A custom Inference Endpoint URL. |
... |
Additional arguments (currently unused). |
The default model, 'Helsinki-NLP/opus-mt-en-fr', translates English to French and is chosen for easy onboarding: it is small, fast, broadly known, and encodes the translation direction in the model ID, so 'hf_translate("Hello")' works with no extra arguments. To translate a different language pair, swap in another Helsinki-NLP 'opus-mt-*' model (for example '"Helsinki-NLP/opus-mt-en-es"' for English to Spanish).
Translation models vary in how they expect languages to be specified. Language-pair models such as the Helsinki-NLP 'opus-mt-*' family encode the direction in the model ID and ignore 'source'/'target'. Multilingual models such as NLLB ('facebook/nllb-200-distilled-600M') instead require 'source' and 'target' to be set to FLORES-200 codes (for example "eng_Latn", "fra_Latn").
A tibble with columns: text, translation.
https://huggingface.co/docs/inference-providers/tasks/translation
## Not run:
# Simplest call: English to French with the default model
hf_translate("Hello, how are you?")
# A different language pair (English to Spanish)
hf_translate("Hello, how are you?", model = "Helsinki-NLP/opus-mt-en-es")
# Multilingual model (FLORES-200 codes)
hf_translate(
"Hello, how are you?",
model = "facebook/nllb-200-distilled-600M",
source = "eng_Latn",
target = "fra_Latn"
)
## End(Not run)
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