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NithinReddyG
/
PhyChip-SmolLM3-3B-base-GRPO-v3

Text Generation
PEFT
Safetensors
lora
analog-circuit-design
spice
ngspice
rlvr
grpo
phychip
conversational
Model card Files Files and versions
xet
Community

Instructions to use NithinReddyG/PhyChip-SmolLM3-3B-base-GRPO-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • PEFT

    How to use NithinReddyG/PhyChip-SmolLM3-3B-base-GRPO-v3 with PEFT:

    from peft import PeftModel
    from transformers import AutoModelForCausalLM
    
    base_model = AutoModelForCausalLM.from_pretrained("HuggingFaceTB/SmolLM3-3B-Base")
    model = PeftModel.from_pretrained(base_model, "NithinReddyG/PhyChip-SmolLM3-3B-base-GRPO-v3")
  • Notebooks
  • Google Colab
  • Kaggle
PhyChip-SmolLM3-3B-base-GRPO-v3
121 MB
Ctrl+K
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  • 1 contributor
History: 2 commits
NithinReddyG's picture
NithinReddyG
PhyChip base-vs-instruct study: adapter + hyper-accurate card
453e867 verified 4 months ago
  • .gitattributes
    1.52 kB
    initial commit 4 months ago
  • README.md
    2.95 kB
    PhyChip base-vs-instruct study: adapter + hyper-accurate card 4 months ago
  • adapter_config.json
    1.11 kB
    PhyChip base-vs-instruct study: adapter + hyper-accurate card 4 months ago
  • adapter_model.safetensors
    121 MB
    xet
    PhyChip base-vs-instruct study: adapter + hyper-accurate card 4 months ago
  • chat_template.jinja
    5.6 kB
    PhyChip base-vs-instruct study: adapter + hyper-accurate card 4 months ago