Text Generation
PEFT
Safetensors
English
lora
fine-tuned-model
instruction-tuning
adaptation
parameter-efficient-finetuning
conversational
Instructions to use npc0/directional-embedder-v0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use npc0/directional-embedder-v0.3 with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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library_name: peft
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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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- lora
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- fine-tuned-model
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- instruction-tuning
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- adaptation
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- parameter-efficient-finetuning
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metrics:
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- perplexity
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- bleu
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- rouge
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datasets:
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- iohadrubin/wikitext-103-raw-v1
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base_model:
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- Qwen/Qwen3-Embedding-0.6B
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---
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# dirlora-v3
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`dirlora-v3` is a LoRA-adapted model checkpoint built for concise, instruction-style text generation with
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improved in-context behavior on targeted tasks.
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## Model details
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- **Model type:** Causal Language Model (LoRA adapter)
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- **Base model:** `Qwen/Qwen3-Embedding-0.6B`
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- **Fine-tuning method:** LoRA / PEFT
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- **LoRA config:**
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- Rank (`r`): `16`
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- Alpha (`alpha`): `{{alpha}}`
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- Dropout: `{{lora_dropout}}`
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- **Training data:** subset of `wikitext 103` for PoC
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- **Framework:** PyTorch + Hugging Face `transformers` + `peft`
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## Intended use
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Use this model for:
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- text embedding
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- experimenting direction/sequence aware embedding
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## Not intended for
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- any engineering solution
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## Usage
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```python
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer("npc0/Qwen3-Embedding-0.6B-OED")
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sentences = [
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"The weather is lovely today.",
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"It's so sunny outside!",
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"He drove to the stadium."
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]
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embeddings = model.encode(sentences)
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similarities = model.similarity(embeddings, embeddings)
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print(similarities.shape)
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```
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## Limitations
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- This is early stage PoC not converged but made progress comparing to previous versions
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| 配置 | R@1 | R@5 | R@20 | MRR | med |
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|---|---|---|---|---|---|
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| **dirlora-v3 + next** | **0.110** | **0.297** | **0.505** | **0.200** | **20** |
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| dirlora-v3 + prev(對照) | 0.043 | 0.167 | 0.368 | 0.114 | 41 |
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| dirlora-v3 無 prompt | 0.058 | 0.210 | 0.418 | 0.137 | 31 |
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| dirlora-v1(前最佳) | 0.075 | 0.242 | 0.465 | 0.162 | 27 |
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| base | 0.046 | 0.150 | 0.318 | 0.108 | 53 |
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## Citation
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If you use this model, please cite:
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```
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@misc{npc0directionalembedderv0.3,
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title={Directional Embedder v0.3},
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author={NPC0},
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year={2026},
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url={https://huggingface.co/npc0/directional-embedder-v0.3},
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}
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```
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