Text Generation
PEFT
Safetensors
English
lora
sft
trl
script-generation
minimax-h3
video-generation
conversational
Instructions to use woodfireind/H3-ScriptGen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use woodfireind/H3-ScriptGen with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-0.8B") model = PeftModel.from_pretrained(base_model, "woodfireind/H3-ScriptGen") - Notebooks
- Google Colab
- Kaggle
File size: 470 Bytes
7dbeac1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"base_model": "Qwen/Qwen3.5-0.8B",
"init_from": "/home/bbear/Documents/OlympusServer/models/script-lora/final",
"lora_r": 16,
"lora_alpha": 32,
"epochs": 2,
"learning_rate": 0.0001,
"max_seq_length": 1536,
"dataset": "/home/bbear/Documents/OlympusServer/models/script-lora/h3-format/train_dataset.full.jsonl",
"dataset_rows": 836,
"format": "minimax-h3-fl2va-v1",
"scriptlib": "/home/bbear/Documents/OlympusServer/models/script-lora/scriptlib"
}
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