Update README.md

README.md

@@ -1,3 +1,69 @@
----
-license: llama3.1
----
+---
+license: apache-2.0
+language:
+- en
+base_model:
+- meta-llama/Meta-Llama-3.1-8B
+---
+# 🦙 Llama3.1-8b-vision-audio Model Card
+
+## Model Details
+
+This repository contains a version of the [LLaVA](https://github.com/haotian-liu/LLaVA) model that supports image and audio input from the [Llama 3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) foundation model using the [PKU-Alignment/align-anything](https://github.com/PKU-Alignment/align-anything) library.
+
+- **Developed by:** the [PKU-Alignment](https://github.com/PKU-Alignment) Team.
+- **Model Type:** An auto-regressive language model based on the transformer architecture.
+- **License:** Non-commercial license.
+- **Fine-tuned from model:** [meta-llama/Llama 3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B).
+
+## Model Sources
+
+- **Repository:** <https://github.com/PKU-Alignment/align-anything>
+- **Dataset:**
+  - <https://huggingface.co/datasets/liuhaotian/LLaVA-Instruct-150K>
+  - <https://huggingface.co/datasets/PKU-Alignment/Align-Anything-Instruction-100K>
+  - <https://huggingface.co/datasets/cvssp/WavCaps>
+
+## How to use model (reprod.)
+
+- Using align-anything
+
+```python
+from align_anything.models.llama_vision_audio_model import (
+    LlamaVisionAudioForConditionalGeneration,
+    LlamaVisionAudioProcessor,
+)
+import torch
+import torchaudio
+from PIL import Image
+
+path = <path_to_model_dir>
+processor = LlamaVisionAudioProcessor.from_pretrained(path)
+model = LlamaVisionAudioForConditionalGeneration.from_pretrained(path)
+
+prompt = "<|start_header_id|>user<|end_header_id|>: Where is the capital of China?\n<|start_header_id|>assistant<|end_header_id|>: "
+
+inputs = processor(text=prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=1024)
+print(processor.decode(outputs[0], skip_special_tokens=True))
+
+prompt = "<|start_header_id|>user<|end_header_id|>: Summarize the audio's contents.<audio>\n<|start_header_id|>assistant<|end_header_id|>: "
+
+audio_path = "align-anything/assets/test_audio.wav"
+audio, _ = torchaudio.load(audio_path)
+if audio.shape[0] == 2:
+    audio = audio.mean(dim=0, keepdim=True)
+audio = audio.squeeze().tolist()
+
+inputs = processor(text=prompt, raw_speech=audio, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=1024)
+print(processor.decode(outputs[0], skip_special_tokens=False))
+
+prompt = "<|start_header_id|>user<|end_header_id|>: <image> Give an overview of what's in the image.\n<|start_header_id|>assistant<|end_header_id|>: "
+image_path = "align-anything/assets/test_image.webp"
+image = Image.open(image_path)
+
+inputs = processor(text=prompt, images=image, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=1024)
+print(processor.decode(outputs[0], skip_special_tokens=True))
+```