unsloth/Llama-3.2-11B-Vision-Instruct (Fine-Tuned)
Model Overview
This model, fine-tuned from the unsloth/Llama-3.2-11B-Vision-Instruct
base, is optimized for vision-language tasks with enhanced instruction-following capabilities. Fine-tuning was completed 2x faster using the Unsloth framework combined with Hugging Face's TRL library, ensuring efficient training while maintaining high performance.
Key Information
- Developed by: Daemontatox
- Base Model:
unsloth/Llama-3.2-11B-Vision-Instruct
- License: Apache-2.0
- Language: English (
en
) - Frameworks Used: Hugging Face Transformers, Unsloth, and TRL
Performance and Use Cases
This model is ideal for applications involving:
- Vision-based text generation and description tasks
- Instruction-following in multimodal contexts
- General-purpose text generation with enhanced reasoning
Features
- 2x Faster Training: Leveraging the Unsloth framework for accelerated fine-tuning.
- Multimodal Capabilities: Enhanced to handle vision-language interactions.
- Instruction Optimization: Tailored for improved comprehension and execution of instructions.
How to Use
Inference Example (Hugging Face Transformers)
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Daemontatox/finetuned-llama-3.2-vision-instruct")
model = AutoModelForCausalLM.from_pretrained("Daemontatox/finetuned-llama-3.2-vision-instruct")
input_text = "Describe the image showing a sunset over mountains."
inputs = tokenizer(input_text, return_tensors="pt")
outputs = model.generate(**inputs, max_length=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/Daemontatox__DocumentCogito-details)!
Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=Daemontatox%2FDocumentCogito&sort[column]=Average%20%E2%AC%86%EF%B8%8F&sort[direction]=desc)!
| Metric |Value (%)|
|-------------------|--------:|
|**Average** | 24.21|
|IFEval (0-Shot) | 50.64|
|BBH (3-Shot) | 29.79|
|MATH Lvl 5 (4-Shot)| 16.24|
|GPQA (0-shot) | 8.84|
|MuSR (0-shot) | 8.60|
|MMLU-PRO (5-shot) | 31.14|
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Model tree for Daemontatox/DocumentCogito
Base model
meta-llama/Llama-3.2-11B-Vision-Instruct
Finetuned
unsloth/Llama-3.2-11B-Vision-Instruct
Spaces using Daemontatox/DocumentCogito 2
Evaluation results
- averaged accuracy on IFEval (0-Shot)Open LLM Leaderboard50.640
- normalized accuracy on BBH (3-Shot)test set Open LLM Leaderboard29.790
- exact match on MATH Lvl 5 (4-Shot)test set Open LLM Leaderboard16.240
- acc_norm on GPQA (0-shot)Open LLM Leaderboard8.840
- acc_norm on MuSR (0-shot)Open LLM Leaderboard8.600
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard31.140