Upload lightonai_LightOnOCR-2-1B_1.txt with huggingface_hub
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lightonai_LightOnOCR-2-1B_1.txt
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```CODE:
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# Load model directly
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from transformers import AutoProcessor, AutoModelForSeq2SeqLM
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processor = AutoProcessor.from_pretrained("lightonai/LightOnOCR-2-1B")
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model = AutoModelForSeq2SeqLM.from_pretrained("lightonai/LightOnOCR-2-1B")
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messages = [
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{
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"role": "user",
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"content": [
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{"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
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{"type": "text", "text": "What animal is on the candy?"}
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]
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},
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]
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inputs = processor.apply_chat_template(
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messages,
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add_generation_prompt=True,
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tokenize=True,
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return_dict=True,
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return_tensors="pt",
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).to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=40)
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print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
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```
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ERROR:
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Traceback (most recent call last):
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File "/tmp/lightonai_LightOnOCR-2-1B_10E2kMg.py", line 27, in <module>
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model = AutoModelForSeq2SeqLM.from_pretrained("lightonai/LightOnOCR-2-1B")
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File "/tmp/.cache/uv/environments-v2/ee91f5fd6c657f04/lib/python3.13/site-packages/transformers/models/auto/auto_factory.py", line 607, in from_pretrained
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raise ValueError(
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...<2 lines>...
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)
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ValueError: Unrecognized configuration class <class 'transformers.models.mistral3.configuration_mistral3.Mistral3Config'> for this kind of AutoModel: AutoModelForSeq2SeqLM.
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Model type should be one of BartConfig, BigBirdPegasusConfig, BlenderbotConfig, BlenderbotSmallConfig, EncoderDecoderConfig, FSMTConfig, GPTSanJapaneseConfig, GraniteSpeechConfig, LEDConfig, LongT5Config, M2M100Config, MarianConfig, MBartConfig, MT5Config, MvpConfig, NllbMoeConfig, PegasusConfig, PegasusXConfig, PLBartConfig, ProphetNetConfig, Qwen2AudioConfig, SeamlessM4TConfig, SeamlessM4Tv2Config, SwitchTransformersConfig, T5Config, T5GemmaConfig, UMT5Config, VoxtralConfig, XLMProphetNetConfig.
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