Instructions to use WindyTranslate/translate-lua-es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WindyTranslate/translate-lua-es 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="WindyTranslate/translate-lua-es")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("WindyTranslate/translate-lua-es") model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-lua-es", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Promote lora build from WindstormLabs/translate-lua-es, with attribution and change statement
Browse files- .gitattributes +2 -0
- README.md +57 -0
- config.json +56 -0
- generation_config.json +16 -0
- model.safetensors +3 -0
- source.spm +3 -0
- special_tokens_map.json +5 -0
- target.spm +3 -0
- tokenizer_config.json +38 -0
- 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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source.spm filter=lfs diff=lfs merge=lfs -text
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target.spm filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: apache-2.0
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base_model: Helsinki-NLP/opus-mt-lua-es
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library_name: transformers
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pipeline_tag: translation
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tags:
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- translation
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- marian
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---
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# translate-lua-es
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Machine translation model, `lua` to `es`, published by Windstorm Labs.
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## Attribution
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Derived from [`Helsinki-NLP/opus-mt-lua-es`](https://huggingface.co/Helsinki-NLP/opus-mt-lua-es), licensed **apache-2.0**.
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Windstorm Labs did not train the original model. This notice provides the attribution the
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licence requires.
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## What was changed
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**The weights in this repository have been modified from the original.** A LoRA fine-tune trained on parallel corpus data and merged into the base weights.
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| | |
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|---|---|
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| Method | `lora-fog` |
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| Tensors modified | **36 of 254** |
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| Max absolute weight delta | **6.614e-05** |
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| Verified | tensor-by-tensor against the upstream original, 2026-07-26 |
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The comparison is tensor-level rather than file-level: safetensors and PyTorch `.bin`
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containers hash differently even when the tensors inside are identical, so a file-hash
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mismatch would prove nothing.
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## Contents
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A single transformers build in safetensors format, loadable directly:
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```python
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tok = AutoTokenizer.from_pretrained("WindyTranslate/translate-lua-es")
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model = AutoModelForSeq2SeqLM.from_pretrained("WindyTranslate/translate-lua-es")
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batch = tok(["<your text here>"], return_tensors="pt", padding=True)
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print(tok.batch_decode(model.generate(**batch), skip_special_tokens=True))
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```
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Other builds of this pair, including CTranslate2 INT8, are not included in this repository.
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## Limitations
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- A single language direction: `lua` to `es`.
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- **No quality benchmark has been run on this pair.** The weights are verified to differ from
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the original; that is a statement about provenance, not about translation quality.
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- Quality is not monotonic with model size or with the amount of fine-tuning applied.
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config.json
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{
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"_name_or_path": "Helsinki-NLP/opus-mt-lua-es",
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"_num_labels": 3,
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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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"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": 60812,
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"decoder_vocab_size": 60813,
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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": null,
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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": null,
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"num_hidden_layers": 6,
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"pad_token_id": 60812,
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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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"torch_dtype": "float32",
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"transformers_version": "4.45.1",
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"use_cache": true,
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"vocab_size": 60813
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}
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generation_config.json
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{
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"bad_words_ids": [
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[
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60812
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]
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],
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"bos_token_id": 0,
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"decoder_start_token_id": 60812,
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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": 6,
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"pad_token_id": 60812,
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"renormalize_logits": true,
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"transformers_version": "4.45.1"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6fe96f122059fb21b88f14880e8dda86761b644eb85ec577bb5a069be981a909
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size 301371316
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source.spm
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:cbe7059341233a855bd72e95b2fd84acb711b6acd48f5e46b604af5edbaff378
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size 823233
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special_tokens_map.json
ADDED
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{
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"eos_token": "</s>",
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"pad_token": "<pad>",
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"unk_token": "<unk>"
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}
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target.spm
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version https://git-lfs.github.com/spec/v1
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oid sha256:b5bf28c020a04fc922f671f5e121486cb848924b250b7ab78803dc5dd64f9a3b
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size 845457
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tokenizer_config.json
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{
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"added_tokens_decoder": {
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"0": {
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"content": "</s>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"1": {
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"content": "<unk>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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},
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"60812": {
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"content": "<pad>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false,
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"special": true
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}
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},
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"clean_up_tokenization_spaces": false,
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"eos_token": "</s>",
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"model_max_length": 512,
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"pad_token": "<pad>",
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"separate_vocabs": false,
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"source_lang": "lua",
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"sp_model_kwargs": {},
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"target_lang": "es",
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"tokenizer_class": "MarianTokenizer",
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"unk_token": "<unk>"
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}
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vocab.json
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