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NLP-Orange-Problem
/
AttentionSeekers

Image-Text-to-Text
PEFT
Safetensors
vision-language
chart-qa
lora
fine-tuned
conversational
Model card Files Files and versions
xet
Community

Instructions to use NLP-Orange-Problem/AttentionSeekers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use NLP-Orange-Problem/AttentionSeekers with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolVLM2-2.2B-Instruct")
    model = PeftModel.from_pretrained(base_model, "NLP-Orange-Problem/AttentionSeekers")
  • Notebooks
  • Google Colab
  • Kaggle
AttentionSeekers
40.7 MB
Ctrl+K
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  • 1 contributor
History: 6 commits
pes1ug23am016's picture
pes1ug23am016
Update README.md
7373f4c verified 2 months ago
  • .gitattributes
    1.52 kB
    initial commit 2 months ago
  • README.md
    3.08 kB
    Update README.md 2 months ago
  • adapter_config.json
    1.02 kB
    Upload model 2 months ago
  • adapter_model.safetensors
    37.2 MB
    xet
    Upload model 2 months ago
  • chat_template.jinja
    403 Bytes
    Upload processor 2 months ago
  • processor_config.json
    1.58 kB
    Upload processor 2 months ago
  • tokenizer.json
    3.55 MB
    Upload processor 2 months ago
  • tokenizer_config.json
    820 Bytes
    Upload processor 2 months ago