Instructions to use WindstormLabs/translate-pt-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindstormLabs/translate-pt-en 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="WindstormLabs/translate-pt-en")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WindstormLabs/translate-pt-en", dtype="auto") - Notebooks
- Google Colab
- Kaggle
clone from WindyWord/translate-pt-en via HF->HF (ADR-039 Phase C gap-fill)
Browse files- .gitattributes +2 -0
- README.md +53 -0
- lora/config.json +59 -0
- lora/generation_config.json +16 -0
- lora/pytorch_model.bin +3 -0
- lora/source.spm +3 -0
- lora/target.spm +3 -0
- lora/tokenizer_config.json +1 -0
- lora/vocab.json +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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lora/source.spm filter=lfs diff=lfs merge=lfs -text
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lora/target.spm filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: cc-by-4.0
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tags:
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- translation
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- marian
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- windyword
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- portuguese
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- english
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language:
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- pt
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- en
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library_name: transformers
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pipeline_tag: translation
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---
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# WindyWord.ai Translation — Portuguese → English
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**Translates Portuguese (`pt`) text into English (`en`).**
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## Quality & Model Lineage
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- **Tier:** Standard ⭐⭐⭐⭐
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- **Base model:** [Helsinki-NLP/opus-mt-ROMANCE-en](https://huggingface.co/Helsinki-NLP/opus-mt-ROMANCE-en) — 68k+ downloads, multilingual Romance-source model
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- **Architecture:** MarianMT
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- **Note:** Helsinki-NLP does not publish a dedicated Portuguese-only `opus-mt-pt-en` model. Their canonical path for Portuguese-source translation is the multilingual `opus-mt-ROMANCE-en`, which handles Portuguese alongside Italian, Spanish, French, Catalan, and Romanian as source languages. This WindyWord repo wraps the same underlying weights with a Portuguese-specific repo name to satisfy installer / consumer code that expects a `translate-pt-en` artifact.
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For sibling Romance-source pairs use [WindyWord/translate-ROMANCE-en](https://huggingface.co/WindyWord/translate-ROMANCE-en) directly (same underlying model).
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## Available Variants
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| Variant | Description |
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|---|---|
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| `lora/` | **WindyStandard** — production baseline. Helsinki-NLP/opus-mt-ROMANCE-en weights wrapped under the WindyWord pt-en namespace. |
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## Quick Usage
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```python
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from transformers import MarianMTModel, MarianTokenizer
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tokenizer = MarianTokenizer.from_pretrained("WindyWord/translate-pt-en", subfolder="lora")
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model = MarianMTModel.from_pretrained("WindyWord/translate-pt-en", subfolder="lora")
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```
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## Commercial Use
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Visit [windyword.ai](https://windyword.ai) for apps and API access.
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---
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## Provenance & License
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Weights derived from [Helsinki-NLP/opus-mt-ROMANCE-en](https://huggingface.co/Helsinki-NLP/opus-mt-ROMANCE-en) under CC-BY-4.0. Wrapped as a Portuguese-specific entry by WindyWord 2026-04-28 to support installer expectations for a `translate-pt-en` repo. Underlying model is identical to `WindyWord/translate-ROMANCE-en`.
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*Certified by Opus 4.6 Opus-Claw (Dr. C) on Veron-1 (RTX 5090, Mt Pleasant SC).*
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lora/config.json
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{
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"_name_or_path": "/tmp/Helsinki-NLP/opus-mt-ROMANCE-en",
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"activation_dropout": 0.0,
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"activation_function": "swish",
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"add_bias_logits": false,
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"add_final_layer_norm": false,
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"architectures": [
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"MarianMTModel"
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],
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"attention_dropout": 0.0,
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"bad_words_ids": [
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[
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65000
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]
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],
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"bos_token_id": 0,
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"classif_dropout": 0.0,
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"classifier_dropout": 0.0,
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"d_model": 512,
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"decoder_attention_heads": 8,
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"decoder_ffn_dim": 2048,
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"decoder_layerdrop": 0.0,
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"decoder_layers": 6,
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"decoder_start_token_id": 65000,
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"decoder_vocab_size": 65001,
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"dropout": 0.1,
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"encoder_attention_heads": 8,
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"encoder_ffn_dim": 2048,
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"encoder_layerdrop": 0.0,
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"encoder_layers": 6,
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"eos_token_id": 0,
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"forced_eos_token_id": 0,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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},
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"init_std": 0.02,
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"is_encoder_decoder": true,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"max_length": 512,
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"max_position_embeddings": 512,
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"model_type": "marian",
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"normalize_before": false,
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"normalize_embedding": false,
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"num_beams": 4,
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"num_hidden_layers": 6,
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"pad_token_id": 65000,
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"scale_embedding": true,
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"share_encoder_decoder_embeddings": true,
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"static_position_embeddings": true,
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"transformers_version": "4.22.0.dev0",
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"use_cache": true,
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"vocab_size": 65001
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}
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lora/generation_config.json
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{
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"bad_words_ids": [
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[
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65000
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]
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],
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"bos_token_id": 0,
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"decoder_start_token_id": 65000,
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"eos_token_id": 0,
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"forced_eos_token_id": 0,
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"max_length": 512,
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"num_beams": 4,
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"pad_token_id": 65000,
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"renormalize_logits": true,
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"transformers_version": "4.32.0.dev0"
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}
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lora/pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:9d77bbbd43a214959e027ffc8713fbe31f8609d14827fba645f1361ca20a6f3a
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size 312087009
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lora/source.spm
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version https://git-lfs.github.com/spec/v1
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oid sha256:baeab21ec00d0b490382b82499ef0348235c5a8e75de28aec8290adf62b007c4
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size 800087
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lora/target.spm
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version https://git-lfs.github.com/spec/v1
|
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oid sha256:121d4e0a20cda2052945d790d335f421f7bea7fa6b0ff7fbc9112eed5f12036f
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size 779494
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lora/tokenizer_config.json
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{"target_lang": "en", "source_lang": "fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la"}
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lora/vocab.json
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