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README.md
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@@ -39,14 +39,16 @@ See [https://github.com/dpfried/incoder](https://github.com/dpfried/incoder) for
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`model = AutoModelForCausalLM.from_pretrained("facebook/incoder-1B")`
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### Tokenizer
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`tokenizer = AutoTokenizer.from_pretrained("facebook/incoder-1B")
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Note: the incoder-1B and incoder-6B tokenizers are identical, so 'facebook/incoder-6B' could also be used.
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When calling `tokenizer.decode`, it's important to pass `clean_up_tokenization_spaces=False` to avoid removing spaces after punctuation:
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`tokenizer.decode(tokenizer.encode("from ."), clean_up_tokenization_spaces=False)`
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## License
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CC-BY-NC 4.0
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`model = AutoModelForCausalLM.from_pretrained("facebook/incoder-1B")`
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### Tokenizer
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`tokenizer = AutoTokenizer.from_pretrained("facebook/incoder-1B")`
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(Note: the incoder-1B and incoder-6B tokenizers are identical, so 'facebook/incoder-6B' could also be used.)
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When calling `tokenizer.decode`, it's important to pass `clean_up_tokenization_spaces=False` to avoid removing spaces after punctuation. For example:
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`tokenizer.decode(tokenizer.encode("from ."), clean_up_tokenization_spaces=False)`
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(Note: encoding prepends the `<|endoftext|>` token, as this marks the start of a document to our model. This token can be removed from the decoded output by passing `skip_special_tokens=True` to `tokenizer.decode`.)
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## License
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CC-BY-NC 4.0
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