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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: Qwen/Qwen3-8B
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ language:
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+ - en
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+ tags:
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+ - safetensors
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+ - dpo
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+ - preference
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+ - rlhf
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+ - manim
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+ - manim-voiceover
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+ - aos
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+ - code-generation
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+ - animation
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+ - merged
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+ ---
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+
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+ # AOS Qwen3 8B Narrated (DPO Aligned - Merged Safetensors)
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+
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+ Direct Preference Optimization (DPO) aligned full bf16 model for **Manim Community Edition** mathematical and educational animation synthesis with synchronized voiceover narration.
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+
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+ **Model Repository:** [nabin2004/AOS-qwen3-8b-narrated-merged](https://huggingface.co/nabin2004/AOS-qwen3-8b-narrated-merged)
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+
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+ ---
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+
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+ ## Lineage & Provenance
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+
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+ | Role | Artifact / Repository | Description |
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+ |---|---|---|
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+ | **Base LLM** | [`Qwen/Qwen3-8B`](https://huggingface.co/Qwen/Qwen3-8B) | Base causal foundation model |
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+ | **SFT Prior** | [`nabin2004/AOS-qwen3-8b-narrated-adapter`](https://huggingface.co/nabin2004/AOS-qwen3-8b-narrated-adapter) | Continued SFT on 400 synchronized educational voiceover trajectories |
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+ | **DPO Adapter** | [`nabin2004/AOS-qwen3-8b-narrated-dpo`](https://huggingface.co/nabin2004/AOS-qwen3-8b-narrated-dpo) | Direct Preference Optimization adapter ($\beta=0.1$) |
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+ | **Merged Weights** | [`nabin2004/AOS-qwen3-8b-narrated-merged`](https://huggingface.co/nabin2004/AOS-qwen3-8b-narrated-merged) | Full unquantized bfloat16 Safetensors weights (this repo) |
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+ | **GGUF / Ollama** | [`nabin2004/AOS-qwen3-8b-narrated-gguf`](https://huggingface.co/nabin2004/AOS-qwen3-8b-narrated-gguf) | Multi-quantized GGUF (`Q4_K_M`, `Q8_0`) for Ollama & llama.cpp |
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+
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+ ---
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+
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+ ## Alignment Objective
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+
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+ The model was aligned with Direct Preference Optimization (DPO) to strongly prefer generating voiceover-synchronized educational animations:
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+ - **Chosen**: Clean `VoiceoverScene` scripts with speech services (`AOSSpeechService` / `GTTSService`), animation duration tracking (`run_time=tracker.duration`), millisecond-accurate `<bookmark mark='...'/>` tags, and natural phonetic spoken narration.
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+ - **Rejected**: Silent, un-narrated standard `Scene` code.
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+
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+ ---
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+
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+ ## Canonical Code Pattern
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+
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+ ```python
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+ from manim import *
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+ from manim_voiceover import VoiceoverScene
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+ from manim_voiceover.services.gtts import GTTSService
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+
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+ class SigmoidExplanation(VoiceoverScene):
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+ def construct(self):
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+ # Configure speech service
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+ self.set_speech_service(GTTSService())
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+
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+ title = Title("The Sigmoid Activation Function")
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+ ax = Axes(x_range=[-6, 6, 2], y_range=[-0.2, 1.2, 0.5])
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+ curve = ax.plot(lambda x: 1 / (1 + np.exp(-x)), color=BLUE)
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+ dot = Dot(ax.c2p(0, 0.5), color=RED)
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+
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+ with self.voiceover(
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+ text="Let's visualize the sigmoid function. <bookmark mark='AXES'/> We begin by setting up our coordinate system, <bookmark mark='CURVE'/> plotting the characteristic S-shaped curve, <bookmark mark='DOT'/> and marking the midpoint inflection at zero, point five."
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+ ) as tracker:
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+ self.play(Write(title))
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+ self.wait_until_bookmark("AXES")
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+ self.play(Create(ax))
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+ self.wait_until_bookmark("CURVE")
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+ self.play(Create(curve))
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+ self.wait_until_bookmark("DOT")
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+ self.play(FadeIn(dot), run_time=tracker.duration)
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+ self.wait(1)
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+ ```
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+
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+ ---
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+
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+ ## Quickstart Usage
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+
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+ ### Hugging Face Transformers
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+
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+ ```python
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_id = "nabin2004/AOS-qwen3-8b-narrated-merged"
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_id,
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+ torch_dtype=torch.bfloat16,
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+ device_map="auto",
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+ trust_remote_code=True,
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+ )
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+
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+ prompt = "Create a narrated Manim animation explaining the Fourier Transform with voiceover bookmarks."
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+ messages = [
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+ {{"role": "system", "content": "You are an expert mathematical animation assistant specializing in Manim Community Edition and voiceover narration with manim-voiceover. You write complete, self-contained, fully executable Python scripts inheriting from VoiceoverScene."}},
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+ {{"role": "user", "content": prompt}}
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+ ]
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+
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+ text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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+ inputs = tokenizer([text], return_tensors="pt").to(model.device)
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+
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+ outputs = model.generate(
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+ **inputs,
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+ max_new_tokens=2048,
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+ temperature=0.2,
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+ top_p=0.95,
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+ pad_token_id=tokenizer.eos_token_id,
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+ )
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+ print(tokenizer.decode(outputs[0][len(inputs.input_ids[0]):], skip_special_tokens=True))
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+ ```
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+
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+ ### High-Throughput Cloud Serving with vLLM
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+
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+ Serve as a high-performance OpenAI-compatible endpoint:
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+
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+ ```bash
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+ vllm serve nabin2004/AOS-qwen3-8b-narrated-merged \
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+ --port 8000 \
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+ --max-model-len 8192 \
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+ --trust-remote-code
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+ ```
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+
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+ ---
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+
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+ ## Citation & Acknowledgments
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+
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+ Part of the **AOS (Agentic Orchestration System)** project for multi-agent educational video synthesis.
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+ - Base Model: Alibaba Cloud Qwen Team (`Qwen/Qwen3-8B`)
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+ - Animation Engine: Manim Community Edition & `manim-voiceover`
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+ "use_cache": true,
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+ "use_sliding_window": false,
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+ "vocab_size": 151936
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+ }
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+ "split_special_tokens": false,
237
+ "tokenizer_class": "Qwen2Tokenizer",
238
+ "unk_token": null
239
+ }
vocab.json ADDED
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