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--- |
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license: apache-2.0 |
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base_model: unsloth/Meta-Llama-3.1-8B-Instruct |
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tags: |
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- diffusion |
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- language-model |
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- llama |
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- text-generation |
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library_name: transformers |
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pipeline_tag: text-generation |
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--- |
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# Llama-3.1-8B Diffusion Model (LAD) |
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This is a **Language Autoregressive Diffusion (LAD)** model based on Llama-3.1-8B-Instruct. |
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## Features |
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- π― Dual mode: Autoregressive + Diffusion generation |
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- π Cosine noise schedule with 1000 timesteps |
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- π§ LoRA fine-tuning (rank 32) |
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- β‘ Custom diffusion components |
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## Usage |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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model = AutoModelForCausalLM.from_pretrained("rootxhacker/llama3-diffusion") |
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tokenizer = AutoTokenizer.from_pretrained("rootxhacker/llama3-diffusion") |
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# Generate text |
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inputs = tokenizer("The future of AI", return_tensors="pt") |
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outputs = model.generate(**inputs, max_length=100) |
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print(tokenizer.decode(outputs[0])) |
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``` |
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## Training Details |
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- Base: Meta-Llama-3.1-8B-Instruct |
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- Dataset: PatrickHaller/cosmopedia-v2-1B |
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- Framework: Unsloth + Custom Diffusion |
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- Context: 256 tokens |
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- Training: 60% AR + 40% Diffusion |
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Uploaded: 2025-06-08 23:13 |
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