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[docs] Fix image link (#36869)

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* fix image link

* fix

* update

* fix
This commit is contained in:
Steven Liu
2025-03-25 11:34:21 -07:00
committed by GitHub
parent d68a91aebf
commit a844297088
4 changed files with 62 additions and 28 deletions
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4
docs/source/en/processors.md
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@@ -29,8 +29,8 @@ import requests
processor = AutoProcessor.from_pretrained("google/paligemma-3b-pt-224") processor = AutoProcessor.from_pretrained("google/paligemma-3b-pt-224")
prompt = "answer en Where is the cow standing?" prompt = "answer en Where is the cat standing?"
url = "https://huggingface.co/gv-hf/PaliGemma-test-224px-hf/resolve/main/cow_beach_1.png" url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"
image = Image.open(requests.get(url, stream=True).raw) image = Image.open(requests.get(url, stream=True).raw)
inputs = processor(text=prompt, images=image, return_tensors="pt") inputs = processor(text=prompt, images=image, return_tensors="pt")

37
src/transformers/models/gemma3/modeling_gemma3.py
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@@ -1272,20 +1272,37 @@ class Gemma3ForConditionalGeneration(Gemma3PreTrainedModel, GenerationMixin):
>>> import requests >>> import requests
>>> from transformers import AutoProcessor, Gemma3ForConditionalGeneration >>> from transformers import AutoProcessor, Gemma3ForConditionalGeneration
>>> model = Gemma3ForConditionalGeneration.from_pretrained("google/Gemma3-test-224px-hf") >>> model = Gemma3ForConditionalGeneration.from_pretrained("google/gemma-3-4b-it")
>>> processor = AutoProcessor.from_pretrained("google/Gemma3-test-224px-hf") >>> processor = AutoProcessor.from_pretrained("google/gemma-3-4b-it")
>>> prompt = "answer en Where is the cow standing?" >>> messages = [
>>> url = "https://huggingface.co/gv-hf/Gemma3-test-224px-hf/resolve/main/cow_beach_1.png" ... {
>>> image = Image.open(requests.get(url, stream=True).raw) ... "role": "system",
... "content": [
>>> inputs = processor(images=image, text=prompt, return_tensors="pt") ... {"type": "text", "text": "You are a helpful assistant."}
... ]
... },
... {
... "role": "user", "content": [
... {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"},
... {"type": "text", "text": "Where is the cat standing?"},
... ]
... },
... ]
>>> inputs = processor.apply_chat_template(
... messages,
... tokenizer=True,
... return_dict=True,
... return_tensors="pt",
... add_generation_prompt=True
... )
>>> # Generate >>> # Generate
>>> generate_ids = model.generate(**inputs, max_length=30) >>> generate_ids = model.generate(**inputs)
>>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] >>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
"answer en Where is the cow standing?\nbeach" "user\nYou are a helpful assistant.\n\n\n\n\n\nWhere is the cat standing?\nmodel\nBased on the image, the cat is standing in a snowy area, likely outdoors. It appears to"
```""" ```
"""
if (input_ids is None) ^ (inputs_embeds is not None): if (input_ids is None) ^ (inputs_embeds is not None):
raise ValueError("You must specify exactly one of input_ids or inputs_embeds") raise ValueError("You must specify exactly one of input_ids or inputs_embeds")

37
src/transformers/models/gemma3/modular_gemma3.py
View File

@@ -883,20 +883,37 @@ class Gemma3ForConditionalGeneration(PaliGemmaForConditionalGeneration):
>>> import requests >>> import requests
>>> from transformers import AutoProcessor, Gemma3ForConditionalGeneration >>> from transformers import AutoProcessor, Gemma3ForConditionalGeneration
>>> model = Gemma3ForConditionalGeneration.from_pretrained("google/Gemma3-test-224px-hf") >>> model = Gemma3ForConditionalGeneration.from_pretrained("google/gemma-3-4b-it")
>>> processor = AutoProcessor.from_pretrained("google/Gemma3-test-224px-hf") >>> processor = AutoProcessor.from_pretrained("google/gemma-3-4b-it")
>>> prompt = "answer en Where is the cow standing?" >>> messages = [
>>> url = "https://huggingface.co/gv-hf/Gemma3-test-224px-hf/resolve/main/cow_beach_1.png" ... {
>>> image = Image.open(requests.get(url, stream=True).raw) ... "role": "system",
... "content": [
>>> inputs = processor(images=image, text=prompt, return_tensors="pt") ... {"type": "text", "text": "You are a helpful assistant."}
... ]
... },
... {
... "role": "user", "content": [
... {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"},
... {"type": "text", "text": "Where is the cat standing?"},
... ]
... },
... ]
>>> inputs = processor.apply_chat_template(
... messages,
... tokenizer=True,
... return_dict=True,
... return_tensors="pt",
... add_generation_prompt=True
... )
>>> # Generate >>> # Generate
>>> generate_ids = model.generate(**inputs, max_length=30) >>> generate_ids = model.generate(**inputs)
>>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] >>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
"answer en Where is the cow standing?\nbeach" "user\nYou are a helpful assistant.\n\n\n\n\n\nWhere is the cat standing?\nmodel\nBased on the image, the cat is standing in a snowy area, likely outdoors. It appears to"
```""" ```
"""
if (input_ids is None) ^ (inputs_embeds is not None): if (input_ids is None) ^ (inputs_embeds is not None):
raise ValueError("You must specify exactly one of input_ids or inputs_embeds") raise ValueError("You must specify exactly one of input_ids or inputs_embeds")

12
src/transformers/models/paligemma/modeling_paligemma.py
View File

@@ -464,19 +464,19 @@ class PaliGemmaForConditionalGeneration(PaliGemmaPreTrainedModel, GenerationMixi
>>> import requests >>> import requests
>>> from transformers import AutoProcessor, PaliGemmaForConditionalGeneration >>> from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
>>> model = PaliGemmaForConditionalGeneration.from_pretrained("google/PaliGemma-test-224px-hf") >>> model = PaliGemmaForConditionalGeneration.from_pretrained("google/paligemma2-3b-mix-224")
>>> processor = AutoProcessor.from_pretrained("google/PaliGemma-test-224px-hf") >>> processor = AutoProcessor.from_pretrained("google/paligemma2-3b-mix-224")
>>> prompt = "answer en Where is the cow standing?" >>> prompt = "Where is the cat standing?"
>>> url = "https://huggingface.co/gv-hf/PaliGemma-test-224px-hf/resolve/main/cow_beach_1.png" >>> url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/pipeline-cat-chonk.jpeg"
>>> image = Image.open(requests.get(url, stream=True).raw) >>> image = Image.open(requests.get(url, stream=True).raw)
>>> inputs = processor(images=image, text=prompt, return_tensors="pt") >>> inputs = processor(images=image, text=prompt, return_tensors="pt")
>>> # Generate >>> # Generate
>>> generate_ids = model.generate(**inputs, max_length=30) >>> generate_ids = model.generate(**inputs,)
>>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] >>> processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
"answer en Where is the cow standing?\nbeach" "Where is the cat standing?\nsnow"
```""" ```"""
if (input_ids is None) ^ (inputs_embeds is not None): if (input_ids is None) ^ (inputs_embeds is not None):