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Model: reaperdoesntknow/Qwen3-1.7B-Thinking-Distil Source: Original Platform
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---
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- qwen3
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- sft
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- trl
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- knowledge-distillation
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- thinking
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- longwriter
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- convergent-intelligence
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- convergentintel
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- edge
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- distillation
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base_model:
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- reaperdoesntknow/Disctil-Qwen3-1.7B
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datasets:
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- longwriter-6k
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- 0xZee/dataset-CoT-Differential-Equations-636
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- 0xZee/dataset-CoT-Linear-Algebra-667
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---
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# Qwen3-1.7B-Thinking-Distil
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**Extended Reasoning Distillation from Qwen3-30B-A3B-Thinking → 1.7B**
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*Convergent Intelligence LLC: Research Division*
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---
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## What This Is
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The most downloaded model in the Convergent Intelligence portfolio. Qwen3-1.7B-Thinking-Distil captures extended deliberation patterns from the Qwen3-30B-A3B **Thinking** teacher — the variant that generates long-form reasoning chains before committing to an answer — and compresses them into a 1.7B student via supervised fine-tuning on the [longwriter-6k](https://huggingface.co/datasets/longwriter-6k) dataset.
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The Thinking teacher produces the **richest signal** of the three teacher variants in the DistilQwen family (Instruct, Thinking, Coder). Where Instruct distillation captures clean instruction-following and Coder captures hierarchical decomposition, Thinking distillation captures the extended internal monologue — the model reasoning through uncertainty, backtracking, and re-evaluating before arriving at a conclusion. That deliberative depth is what makes this variant the highest-download model in the collection.
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## Architecture
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| Parameter | Value |
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|-----------|-------|
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| Architecture | Qwen3ForCausalLM |
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| Parameters | ~2.03B (1.7B effective) |
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| Hidden Size | 2048 |
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| Layers | 28 |
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| Attention Heads | 16 (Q) / 8 (KV) — GQA |
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| Intermediate | 6144 |
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| Head Dimension | 128 |
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| Context Length | 40,960 tokens (max position) |
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| Vocabulary | 151,936 |
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| Precision | BF16 |
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| Activation | SiLU |
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## Training
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**Teacher:** Qwen3-30B-A3B-Thinking
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**Student:** Qwen3-1.7B
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**Dataset:** longwriter-6k — long-form generation samples that preserve extended reasoning chains
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**Method:** Supervised Fine-Tuning (SFT) via TRL
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| Parameter | Value |
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|-----------|-------|
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| Max Sequence Length | 4,096 |
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| Precision | BF16 |
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| Framework | TRL (SFTTrainer) |
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| Hardware | NVIDIA H100 |
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The training captures the teacher's extended thinking traces through direct SFT rather than logit-level KD. This is a deliberate design choice — the longwriter-6k dataset provides naturally long reasoning samples where the signal is in the structure of the generation (how the teacher approaches, reconsiders, and resolves), not just the final token probabilities.
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For the full topology-aware distillation pipeline (BV decomposition, jump detection, curriculum ordering), see [TopologicalQwen](https://huggingface.co/reaperdoesntknow/TopologicalQwen). This model is the SFT-direct variant — simpler, faster to train, and empirically the most downloaded for a reason: the Thinking teacher's extended chains transfer well through pure SFT.
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## Usage
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained(
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"reaperdoesntknow/Qwen3-1.7B-Thinking-Distil",
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained(
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"reaperdoesntknow/Qwen3-1.7B-Thinking-Distil"
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)
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messages = [
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{"role": "user", "content": "Explain why gradient descent can get stuck in saddle points but not local minima in high dimensions."}
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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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output = model.generate(
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**inputs,
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max_new_tokens=2048,
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do_sample=True,
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top_p=0.9,
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temperature=0.7,
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repetition_penalty=1.15
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)
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print(tokenizer.decode(output[0], skip_special_tokens=True))
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```
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### Generation Tips
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- **Temperature 0.6–0.8** works best for reasoning tasks — low enough for coherence, high enough to activate the extended deliberation patterns from the Thinking teacher.
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- **Repetition penalty 1.1–1.2** prevents the model from getting caught in reasoning loops during long generations.
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- **Max tokens 1024–2048** — the model was trained on 4096 max seq, so it can generate long. Give it room.
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- The model inherits the Thinking teacher's tendency to reason before answering. Let it.
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## Distillation Position
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```
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Qwen3-30B-A3B-Thinking (teacher)
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↓ SFT on longwriter-6k (4096 max seq)
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Qwen3-1.7B-Thinking-Distil ← you are here
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```
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This model is the **direct SFT** path. The DistilQwen collection also includes models that go through additional refinement stages:
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```
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Qwen3-1.7B (base)
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→ Qwen3-1.7B-Distilled-30B-A3B (Instruct teacher KD)
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→ DiStil (uncensored SFT)
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→ Disctil (DISC refinement)
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→ TopologicalQwen (full TKD pipeline)
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```
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Different paths, different capabilities. This model prioritizes extended reasoning. TopologicalQwen prioritizes structural precision. The Coder variant prioritizes hierarchical decomposition. They're complementary.
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## DistilQwen Collection
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| Model | Downloads | What It Does |
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|-------|-----------|-------------|
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| **[Qwen3-1.7B-Thinking-Distil](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Thinking-Distil)** | **1,188** | **← this model. Thinking teacher SFT.** |
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| [TopologicalQwen](https://huggingface.co/reaperdoesntknow/TopologicalQwen) | 1,134 | Full TKD pipeline. BV decomposition + DualMind format. |
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| [DiStil-Qwen3-1.7B-uncensored](https://huggingface.co/reaperdoesntknow/DiStil-Qwen3-1.7B-uncensored) | 1,030 | DISC-informed uncensored distillation. |
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| [Qwen3-1.7B-Coder-Distilled-SFT](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Coder-Distilled-SFT) | 966 | Coder teacher. Hierarchical problem solving. |
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| [DistilQwen3-1.7B-uncensored](https://huggingface.co/reaperdoesntknow/DistilQwen3-1.7B-uncensored) | 832 | Base uncensored variant. |
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|
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Full collection: [DistilQwen on HuggingFace](https://huggingface.co/collections/reaperdoesntknow/distilqwen-69bf40ec669117e3f069ef1c)
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## Methodology
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Full methodology paper: **[Structure Over Scale: Proof-Weighted Knowledge Distillation](https://doi.org/10.57967/hf/8165)** (DOI: 10.57967/hf/8165)
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Companion paper: **[Three Teachers to Dual Cognition](https://doi.org/10.57967/hf/8184)** (DOI: 10.57967/hf/8184) — covers the DualMind extension and ghost imprinting phenomenon.
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## License
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Apache 2.0 — same as the base Qwen3 model.
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## Mathematical Foundations: Discrepancy Calculus (DISC)
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This model's training pipeline is grounded in Discrepancy Calculus — a measure-theoretic framework that treats singularities as primary structure rather than pathology. Full theory: *"On the Formal Analysis of Discrepancy Calculus"* (Colca, 2026; Convergent Intelligence LLC: Research Division).
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**The Core Operator:**
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$$Df(x) = \lim_{\varepsilon \downarrow 0} \frac{1}{\varepsilon} \int_x^{x+\varepsilon} \frac{|f(t) - f(x)|}{|t - x|}\, dt$$
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For smooth $f$: $Df(x) = |f'(x)|$. For rough $f$: $D$ localizes irregularity to null sets while preserving integral structure.
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**The Mesh Fundamental Identity** — every BV function decomposes as:
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$$f(b) - f(a) = \underbrace{\int_a^b f'(x)\,dx}_{\text{smooth (AC)}} + \underbrace{\sum_{x \in J_f} \Delta f(x)}_{\text{jumps}} + \underbrace{D^c f(I)}_{\text{Cantor drift}}$$
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Standard knowledge distillation captures only term 1. Topological Knowledge Distillation (TKD) preserves all three by treating the teacher's output distribution as a BV function and computing discrepancy energy, jump sets, and gap energy density before training begins.
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## Citation
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```bibtex
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@misc{colca2026distilqwen,
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title={Structure Over Scale: Proof-Weighted Knowledge Distillation from Qwen3-30B to 1.7B},
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author={Colca, Roy},
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year={2026},
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doi={10.57967/hf/8165},
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publisher={Convergent Intelligence LLC: Research Division}
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}
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```
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---
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*Convergent Intelligence LLC: Research Division — 49 models, 22,598 downloads across the portfolio.*
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*[Full portfolio](https://huggingface.co/reaperdoesntknow) | [DistilQwen Collection](https://huggingface.co/collections/reaperdoesntknow/distilqwen-69bf40ec669117e3f069ef1c) | [DualMind Collection](https://huggingface.co/collections/reaperdoesntknow/dualmind-69c93f888c6e79ecc69cf41e)*
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---
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## Convergent Intelligence Portfolio
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|
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*Part of the [DistilQwen Series](https://huggingface.co/collections/reaperdoesntknow/distilqwen-69bf40ec669117e3f069ef1c) by [Convergent Intelligence LLC: Research Division](https://huggingface.co/reaperdoesntknow)*
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### Related Models
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|
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| Model | Downloads | Format |
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|-------|-----------|--------|
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| [TopologicalQwen](https://huggingface.co/reaperdoesntknow/TopologicalQwen) | 1,974 | BF16 |
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| [Qwen3-1.7B-Thinking-Distil](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Thinking-Distil) | 1,903 | BF16 |
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| [Qwen3-1.7B-Coder-Distilled-SFT](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Coder-Distilled-SFT) | 1,677 | BF16 |
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| [DiStil-Qwen3-1.7B-uncensored](https://huggingface.co/reaperdoesntknow/DiStil-Qwen3-1.7B-uncensored) | 1,602 | BF16 |
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| [DistilQwen3-1.7B-uncensored](https://huggingface.co/reaperdoesntknow/DistilQwen3-1.7B-uncensored) | 1,574 | BF16 |
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| [Qwen3-1.7B-Distilled-30B-A3B](https://huggingface.co/reaperdoesntknow/Qwen3-1.7B-Distilled-30B-A3B) | 1,138 | BF16 |
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### Papers
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| Paper | DOI |
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|-------|-----|
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| [Structure Over Scale](https://huggingface.co/reaperdoesntknow/Structure-Over-Scale) | 10.57967/hf/8165 |
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| [Three Teachers to Dual Cognition](https://huggingface.co/reaperdoesntknow/DualMind_Methodolgy) | 10.57967/hf/8184 |
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| [Discrepancy Calculus](https://huggingface.co/reaperdoesntknow/Discrepancy_Calculus) | 10.57967/hf/8194 |
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---
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*Last updated: 2026-03-31 by Convergent Intelligence LLC: Research Division*
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<!-- cix-keeper-ts:2026-06-12T13:16:41Z -->
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is string %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
|
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{{- '\n' }}
|
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{%- endif %}
|
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{%- if tool_call.function %}
|
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{%- set tool_call = tool_call.function %}
|
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{%- endif %}
|
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
|
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{{- '", "arguments": ' }}
|
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{%- if tool_call.arguments is string %}
|
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
|
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{%- endif %}
|
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{{- '<|im_end|>\n' }}
|
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{%- elif message.role == "tool" %}
|
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
|
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{%- endif %}
|
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{%- endfor %}
|
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{%- if add_generation_prompt %}
|
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{{- '<|im_start|>assistant\n' }}
|
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{%- if enable_thinking is defined and enable_thinking is false %}
|
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{{- '<think>\n\n</think>\n\n' }}
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{%- endif %}
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{%- endif %}
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63
config.json
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config.json
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{
|
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"architectures": [
|
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"Qwen3ForCausalLM"
|
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],
|
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"attention_bias": false,
|
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"attention_dropout": 0.0,
|
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"bos_token_id": null,
|
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"dtype": "bfloat16",
|
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"eos_token_id": 151645,
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"head_dim": 128,
|
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"hidden_act": "silu",
|
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"hidden_size": 2048,
|
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"initializer_range": 0.02,
|
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"intermediate_size": 6144,
|
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"layer_types": [
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 40960,
|
||||
"max_window_layers": 28,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 28,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": 151643,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_parameters": {
|
||||
"rope_theta": 1000000,
|
||||
"rope_type": "default"
|
||||
},
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": false,
|
||||
"transformers_version": "5.0.0",
|
||||
"use_cache": false,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
12
generation_config.json
Normal file
12
generation_config.json
Normal file
@@ -0,0 +1,12 @@
|
||||
{
|
||||
"do_sample": true,
|
||||
"eos_token_id": [
|
||||
151645,
|
||||
151643
|
||||
],
|
||||
"pad_token_id": 151643,
|
||||
"temperature": 0.6,
|
||||
"top_k": 20,
|
||||
"top_p": 0.95,
|
||||
"transformers_version": "5.0.0"
|
||||
}
|
||||
3
model.safetensors
Normal file
3
model.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:13f028a8b0dce70cbbc42b182b374235f38b395893e827dbdb11bfbb0a1cc052
|
||||
size 4063515640
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
|
||||
size 11422650
|
||||
29
tokenizer_config.json
Normal file
29
tokenizer_config.json
Normal file
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
"<|object_ref_end|>",
|
||||
"<|box_start|>",
|
||||
"<|box_end|>",
|
||||
"<|quad_start|>",
|
||||
"<|quad_end|>",
|
||||
"<|vision_start|>",
|
||||
"<|vision_end|>",
|
||||
"<|vision_pad|>",
|
||||
"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"is_local": false,
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
Reference in New Issue
Block a user