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Model: pattlr13/Llama-Legal-Expression-8B-v0.1-merged Source: Original Platform
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README.md
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README.md
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---
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language:
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- en
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base_model:
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- meta-llama/Llama-3.1-8B-Instruct
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pipeline_tag: text-generation
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tags:
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- llama
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- legal
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- marketing
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- qlora
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- axolotl
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---
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## Model summary
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| | |
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|--|--|
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| **Type** | Causal LM (merged full weights: base + LoRA) |
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| **Base model** | [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) |
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| **Task** | Short-form **legal marketing** and **client-facing** copy (website-style tone, practice descriptions, alerts-style prose) |
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| **Training** | Supervised fine-tuning (**QLoRA** via [Axolotl](https://github.com/axolotl-ai-cloud/axolotl)); LoRA adapters merged into the base for serving |
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| **Language** | English |
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| **License** | Use of **Llama** weights is subject to **Meta’s Llama license** and Hugging Face acceptance flow. This adapter/merged artifact is shared under the terms you set on the Hub; the **GitHub project** uses MIT for code/docs—see repo `LICENSE` / `NOTICE`. |
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## Intended use
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- Drafting or refining **marketing-oriented** legal content (e.g. practice blurbs, client-facing summaries).
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- **Not** for legal advice, regulated filings, or high-stakes decisions without human review.
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## Training data (high level)
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- Data came from **public** law-firm web marketing pages across many large-firm domains, plus an **LLM-assisted curation** step to standardize tone and structure into chat-format SFT pairs.
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- **Raw scrapes and full training JSONL are not redistributed** with the GitHub project; statistics and methodology are described in the linked repository.
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## Limitations
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- **Style and fluency**, not factual grounding: the model can still hallucinate or misstate facts; always verify against sources and counsel.
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- Strongest fit for **external-facing, polished** marketing tone; may be less ideal for purely operational or highly technical internal briefs.
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- **Bias and safety:** inherits behaviors and limitations of the base Llama 3.1 instruct model; apply usual content policies.
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## How to reproduce / cite the project
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- GitHub (configs, scripts, evaluation examples): link your public **`fine-tuning-llama-public`** repository when published.
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- Base model and Axolotl citations should follow their respective licenses and papers/docs.
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## Inference
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- Suitable for **vLLM**, **Transformers**, or other Llama-compatible stacks; use the same chat template / tokenizer as **Meta-Llama-3.1-8B-Instruct** unless your serving stack overrides it.
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---
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*This file lives in the GitHub repo as documentation to paste into the Hub; the canonical model page is on Hugging Face.*
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