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fix typos in idefics.md (#26648)

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* fix typos in idefics.md

Two typos found in reviewing this documentation.

1) max_new_tokens=4, is not sufficient to generate "Vegetables" as indicated - you will get only "Veget". (incidentally - some mention of how to select this value might be useful as it seems to change in each example)

2) inputs = processor(prompts, return_tensors="pt").to(device) as inputs need to be on the same device (as they are in all other examples on the page)

* Update idefics.md

Change device to cuda explicitly to match other examples
This commit is contained in:
tom white
2023-10-09 23:18:02 +13:00
committed by GitHub
parent 740fc6a1da
commit c7f01beece
1 changed files with 2 additions and 2 deletions
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docs/source/en/tasks/idefics.md
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@@ -276,7 +276,7 @@ We can instruct the model to classify the image into one of the categories that
>>> inputs = processor(prompt, return_tensors="pt").to("cuda")
>>> bad_words_ids = processor.tokenizer(["<image>", "<fake_token_around_image>"], add_special_tokens=False).input_ids
>>> generated_ids = model.generate(**inputs, max_new_tokens=4, bad_words_ids=bad_words_ids)
>>> generated_ids = model.generate(**inputs, max_new_tokens=6, bad_words_ids=bad_words_ids)
>>> generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)
>>> print(generated_text[0])
Instruction: Classify the following image into a single category from the following list: ['animals', 'vegetables', 'city landscape', 'cars', 'office'].
@@ -357,7 +357,7 @@ for a batch of examples by passing a list of prompts:
... ],
... ]
>>> inputs = processor(prompts, return_tensors="pt")
>>> inputs = processor(prompts, return_tensors="pt").to("cuda")
>>> bad_words_ids = processor.tokenizer(["<image>", "<fake_token_around_image>"], add_special_tokens=False).input_ids
>>> generated_ids = model.generate(**inputs, max_new_tokens=10, bad_words_ids=bad_words_ids)