ZhenZeng
S-MLLMUn-llava-onevision-qwen2-7b-original
Run this model inference on single tenant GPU with unmatched speed and reliability at scale.
Get help setting up a custom Dedicated Endpoints.
Talk with our engineer to get a quote for reserved GPU instances with discounts.
README
S-MLLMUn LLaVA-OneVision Original Model
This repository contains the fine-tuned original LLaVA-OneVision checkpoint used by S-MLLMUn before applying unlearning methods.
The checkpoint was initialized from llava-hf/llava-onevision-qwen2-7b-si-hf and fine-tuned on the S-MLLMUn benchmark fine-tuning data. Tokenizer and processor files are copied from the base model so the checkpoint can be loaded directly with Transformers.
Usage
python
from transformers import AutoProcessor, LlavaOnevisionForConditionalGenerationmodel_id = "path-or-hf-repo-id"processor = AutoProcessor.from_pretrained(model_id)model = LlavaOnevisionForConditionalGeneration.from_pretrained(model_id)
For benchmark reproduction, place this checkpoint at:
text
model/original_model/llava-onevision-qwen2-7b-original
and pass it as --original_dir in the S-MLLMUn training scripts.
Model provider
ZhenZeng
Model tree
Base
llava-hf/llava-onevision-qwen2-7b-si-hf
Fine-tuned
this model
Modalities
Input
Video, Text, Image
Output
Text
Pricing
Dedicated Endpoints
View detailsSupported Functionality
Model APIs
Dedicated Endpoints
Container
More information