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
File size: 644 Bytes
fd32502 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"audio_token": "<|audio|>",
"boa_token": "<|audio>",
"boi_token": "<|image>",
"bos_token": "<bos>",
"eoa_token": "<audio|>",
"eoc_token": "<channel|>",
"eoi_token": "<image|>",
"eos_token": "<eos>",
"eot_token": "<turn|>",
"escape_token": "<|\"|>",
"etc_token": "<tool_call|>",
"etd_token": "<tool|>",
"etr_token": "<tool_response|>",
"image_token": "<|image|>",
"mask_token": "<mask>",
"pad_token": "<pad>",
"soc_token": "<|channel>",
"sot_token": "<|turn>",
"stc_token": "<|tool_call>",
"std_token": "<|tool>",
"str_token": "<|tool_response>",
"think_token": "<|think|>",
"unk_token": "<unk>"
} |