| from unsloth import FastVisionModel |
| from dotenv import load_dotenv |
| import os |
|
|
|
|
| def save_model(model, tokenizer, local: bool) -> None: |
| load_dotenv() |
| if local: |
| model.save_pretrained() |
| tokenizer.save_pretrained("ft_llava") |
| else: |
| model.push_to_hub(f"{os.getenv("ORG_NAME")}/ft_llava", token = os.getenv("HF_TOKEN")) |
| return |
|
|
|
|
| def save_gguf(model_name: str, local:bool, tokenizer): |
| model, processor = FastVisionModel.from_pretrained( |
| model_name= model_name, |
| load_in_4bit=True, |
| ) |
| FastVisionModel.for_inference(model) |
| if local: |
| model.save_pretrained_merged("ft_qwen2_vl_2b", tokenizer) |
|
|
| else: |
| model.push_to_hub_merged(f"{os.getenv("ORG_NAME")}/ft_qwen2_vl_2b", tokenizer, token = f"{os.getenv("HF_TOKEN")}") |
|
|
