Instructions to use kiki041126/fovis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kiki041126/fovis with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-VL-8B-Instruct") model = PeftModel.from_pretrained(base_model, "kiki041126/fovis") - Notebooks
- Google Colab
- Kaggle
FOVIS
FOVIS SFT LoRA adapter for Qwen/Qwen3-VL-8B-Instruct.
This repository contains the adapter weights. Run the following code from the
FOVIS project environment so that the fovis package is available.
import torch
from peft import PeftModel
from transformers import AutoProcessor, Qwen3VLForConditionalGeneration
from fovis import FOVISConfig, patch_qwen3vl_model, register_fovis
register_fovis(
FOVISConfig(fovis_chunk_size=512, fovis_topk=3),
model_type="qwen3vl",
)
base_model = Qwen3VLForConditionalGeneration.from_pretrained(
"Qwen/Qwen3-VL-8B-Instruct",
torch_dtype=torch.bfloat16,
device_map="cuda:0",
attn_implementation="flash_attention_2",
)
patch_qwen3vl_model(base_model)
model = PeftModel.from_pretrained(
base_model,
"kiki041126/fovis",
torch_dtype=torch.bfloat16,
)
model = model.merge_and_unload()
model.eval()
processor = AutoProcessor.from_pretrained("kiki041126/fovis")
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Base model
Qwen/Qwen3-VL-8B-Instruct