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README.md
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# llama-3.1-8B-vision-378
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##
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```python
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import torch
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```
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```
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.x+=:.
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z` ^% .uef^"
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# llama-3.1-8B-vision-378
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Projection module trained to add vision capabilties to Llama 3 using SigLIP, then applied to LLama-3.1-8B-Instruct. Built by [@yeswondwerr](https://x.com/yeswondwerr) and [@qtnx_](https://x.com/qtnx_).
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## Usage
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```python
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import torch
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)
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```
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## 4-bit quantization
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```python
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import torch
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from PIL import Image
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from transformers import BitsAndBytesConfig
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import requests
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from io import BytesIO
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url = "https://huggingface.co/qresearch/llama-3-vision-alpha-hf/resolve/main/assets/demo-2.jpg"
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response = requests.get(url)
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image = Image.open(BytesIO(response.content))
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bnb_cfg = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_compute_dtype=torch.float16,
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llm_int8_skip_modules=["mm_projector", "vision_model"],
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)
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model = AutoModelForCausalLM.from_pretrained(
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"qresearch/llama-3.1-8B-vision-378",
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trust_remote_code=True,
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torch_dtype=torch.float16,
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quantization_config=bnb_cfg,
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"qresearch/llama-3.1-8B-vision-378",
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use_fast=True,
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)
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print(
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model.answer_question(
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image, "Briefly describe the image", tokenizer, max_new_tokens=128, do_sample=True, temperature=0.3
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),
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)
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```
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```
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.x+=:.
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z` ^% .uef^"
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