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NOTICE ADDED
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+ Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
README.md ADDED
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+ ---
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+ language: [pl]
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+ license: llama3.1
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+ pipeline_tag: text-generation
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+ library_name: llama.cpp
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+ tags:
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+ - gguf
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+ - quantized
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+ - q8_0
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+ - f16
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+ base_model: ARTEXIT/Llama-PLLuM-8B-instruct-ArtexIT-reasoning
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+ base_model_relation: quantized
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+ quantization:
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+ - Q8_0
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+ - Q5_K_M
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+ ---
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+
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+ # Llama-PLLuM-8B-instruct-ArtexIT-reasoning
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+
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+ **Built with Llama**
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+
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+ This repository contains a GRPO fine‑tune of [`CYFRAGOVPL/Llama-PLLuM-8B-instruct`] trained on **GSM8K** (MIT).
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+ We publish both **Hugging Face (safetensors)** and **GGUF** artifacts (Q8_0, Q5_K_M) for use with `llama.cpp`.
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+
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+
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+ ## What is this?
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+ - **Base**: Meta Llama 3.1 → PLLuM 8B Instruct (Polish) → GRPO fine‑tune (math / word problems).
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+ - **Context**: ~131k (based on GGUF header).
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+ - **Message format**: Llama `[INST] ... [/INST]` + explicit reasoning / answer tags (see below).
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+ - **Default chat template**: The tokenizer includes a default system instruction enforcing the two‑block format.
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+
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+
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+ ## Prompt format
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+
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+ The model expects Llama chat formatting and supports explicit tags:
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+
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+ - **Reasoning**: `<think> ... </think>`
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+ - **Final answer**: `<answer> ... </answer>`
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+
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+ **Example**
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+ ```text
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+ [INST] Rozwiąż: 12 * 13 = ? [/INST]
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+ <think>12*13 = 156.</think>
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+ <answer>156</answer>
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+ ```
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+
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+ ## Quickstart
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+
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+ ### Transformers (PyTorch)
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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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+ repo = "ARTEXIT/Llama-PLLuM-8B-instruct-ArtexIT-reasoning"
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+ tok = AutoTokenizer.from_pretrained(repo, use_fast=True)
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+ model = AutoModelForCausalLM.from_pretrained(repo, torch_dtype="auto", device_map="auto")
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+
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+ prompt = tok.apply_chat_template(
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+ [{"role": "user", "content": "Podaj 3 miasta w Polsce."}],
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+ add_generation_prompt=True,
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+ tokenize=False,
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+ )
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+ inputs = tok(prompt, return_tensors="pt").to(model.device)
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+ out = model.generate(**inputs, max_new_tokens=64)
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+ print(tok.decode(out[0], skip_special_tokens=False))
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+ ```
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+
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+
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+ ## Training (brief)
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+
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+ - **Method**: GRPO (policy‑gradient reinforcement learning with multiple reward functions).
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+ - **Data**: `openai/gsm8k` — License: **MIT**.
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+ - **Goal**: consistent two‑block outputs (reasoning + final answer) using the training tags.
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+
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+
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+ ## License & Attribution
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+
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+ This repository contains derivatives of **Llama 3.1** and **PLLuM**:
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+
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+ - **Llama 3.1 Community License** applies. When redistributing, you must:
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+ - include a copy of the license and **prominently display “Built with Llama”**,
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+ - include **“Llama” at the beginning of any distributed model’s name** if it was created, trained or fine‑tuned using Llama materials,
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+ - keep a **NOTICE** file with the following line:
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+ `Llama 3.1 is licensed under the Llama 3.1 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.`
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+ - comply with the **Acceptable Use Policy (AUP)**.
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+ - **PLLuM**: please cite the PLLuM work (see **Citation** below).
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+ - **Data**: GSM8K is MIT‑licensed; include dataset attribution.
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+
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+ This repo includes:
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+ - `LICENSE` — full text of the **Llama 3.1 Community License**
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+ - `USE_POLICY.md` — pointer to the official **Acceptable Use Policy**
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+ - `NOTICE` — required Llama attribution line
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+
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+ > If your (or your affiliates’) products exceeded **700M monthly active users** on the Llama 3.1 release date, you must obtain a separate license from Meta before exercising the rights in the Llama 3.1 license.
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+
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+
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+ ## Citation
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+
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+ If you use PLLuM in research or deployments, please cite:
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+
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+ ```bibtex
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+ @unpublished{pllum2025,
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+ title={PLLuM: A Family of Polish Large Language Models},
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+ author={PLLuM Consortium},
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+ year={2025}
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+ }
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+ ```
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+ # Llama 3.1 Acceptable Use Policy (AUP)
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+
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+ This repository distributes a model derived from Llama 3.1. By accessing or using this model, you agree to the Llama 3.1 Acceptable Use Policy.
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+
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+ **The most recent, authoritative copy of the AUP is maintained by Meta at:**
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+ https://llama.meta.com/llama3_1/use-policy
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+
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+ For convenience only (non-exhaustive summary), the AUP requires responsible and lawful use and prohibits, among other things, uses that:
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+ - Violate laws or regulations;
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+ - Exploit, harm, or endanger people (including harassment, discrimination, or incitement to violence);
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+ - Infringe privacy or intellectual property rights;
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+ - Facilitate creation or distribution of malicious code or high-risk illegal activities.
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+
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+ If this summary conflicts with the official AUP, **the official AUP controls**. Please read the full AUP at the link above before using the model.