Image-Text-to-Text
PEFT
Safetensors
English
gemma4
lora
adapter
math
code
reasoning
step-by-step
verified-data
autoscientist
adaption
negative-result
conversational
Eval Results (legacy)
Instructions to use manifesta/adaption_verified_math_code_instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use manifesta/adaption_verified_math_code_instruct with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-4-31B-it") model = PeftModel.from_pretrained(base_model, "manifesta/adaption_verified_math_code_instruct") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e349a1c67be2ef8c92efb101dd7fcfa37086506d90dff9d319bd31ada80dc3d8
- Size of remote file:
- 43.9 MB
- SHA256:
- 3efb30e9f06457a9dde4acb1c596c5f4f6fa754ab5395e67a3bdbc1db8e06e12
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