Image-Text-to-Text
PEFT
Safetensors
English
lora
qlora
tutoring
education
multimodal
build-small-hackathon
conversational
Instructions to use build-small-hackathon/pocket-tutor-minicpmv-socratic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use build-small-hackathon/pocket-tutor-minicpmv-socratic with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM-V-4.6") model = PeftModel.from_pretrained(base_model, "build-small-hackathon/pocket-tutor-minicpmv-socratic") - Notebooks
- Google Colab
- Kaggle
File size: 1,198 Bytes
6667121 | 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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | {
"image_processor": {
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"downsample_mode": "16x",
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "MiniCPMV4_6ImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"max_slice_nums": 9,
"patch_size": 14,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"scale_resolution": 448,
"slice_mode": true,
"use_image_id": true
},
"processor_class": "MiniCPMV4_6Processor",
"video_processor": {
"do_convert_rgb": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"do_sample_frames": true,
"downsample_mode": "16x",
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"max_num_frames": 128,
"max_slice_nums": 9,
"patch_size": 14,
"resample": 3,
"rescale_factor": 0.00392156862745098,
"return_metadata": false,
"scale_resolution": 448,
"slice_mode": true,
"stack_frames": 1,
"use_image_id": true,
"video_processor_type": "MiniCPMV4_6VideoProcessor"
}
}
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