Translation
Transformers
Safetensors
multilingual
m2m_100
text2text-generation
nllb
seq2seq
endpoints-template
Instructions to use ericaRC/example with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ericaRC/example 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="ericaRC/example")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ericaRC/example") model = AutoModelForSeq2SeqLM.from_pretrained("ericaRC/example", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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model_loader: point REPO at ericaRC/example and include TROUBLESHOOTING.md
Previous value (Resilient-Coders/baseline-nllb) was the pre-migration target and would 403 for anyone re-running the script. Also adds TROUBLESHOOTING.md to ENDPOINT_FILES so it gets pushed by push_endpoint_files(), and refreshes the login hint to `hf auth login` since `huggingface-cli` is deprecated. Made-with: Cursor133d507 -
README: link to TROUBLESHOOTING.md
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Add TROUBLESHOOTING.md documenting real deploy failures
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Pin transformers<5 so extra_special_tokens schema stays compatible
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Fix tokenizer_config: move lang codes to additional_special_tokens for transformers<5 compat
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Update README.md
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Upload M2M100ForConditionalGeneration
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Upload tokenizer
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Upload folder using huggingface_hub
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initial commit
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