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Model: HattoriHanzo1/Liquid-LFM2-8B-Polish-Warrior Source: Original Platform
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Liquid-LFM2-8B-Polish-F16.gguf filter=lfs diff=lfs merge=lfs -text
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Liquid-LFM2-8B-Polish-Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
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Liquid-LFM2-8B-Polish-F16.gguf
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Liquid-LFM2-8B-Polish-F16.gguf
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Liquid-LFM2-8B-Polish-Q4_K_M.gguf
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Liquid-LFM2-8B-Polish-Q4_K_M.gguf
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Liquid-LFM2-8B-Polish-Q6_K.gguf
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Liquid-LFM2-8B-Polish-Q6_K.gguf
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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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- pl
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- en
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license: apache-2.0
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base_model: LiquidAI/LFM2-8B-A1B
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library_name: transformers
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tags:
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- liquid
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- lfm
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- polish
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- technical
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- electronics
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- programming
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- gguf
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- warrior-of-silicon
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- hattori-hanzo
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- moe
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- quantized
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metrics:
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- loss
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---
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# ⚔️ Liquid-LFM2-8B-Polish-Warrior (Hattori Hanzo Edition)
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### 📥 Szybkie Pobieranie (GGUF)
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Wersje zoptymalizowane do działania na domowym sprzęcie (Llama.cpp, LM Studio, Ollama):
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| Model | Rozmiar | Opis | Link |
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| :--- | :--- | :--- | :--- |
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| **Q6_K** | ~6.7 GB | Najwyższa jakość, minimalna strata precyzji | [Pobierz Q6](https://huggingface.co/Michal1981/Liquid-LFM2-8B-Polish-Warrior/resolve/main/Liquid-LFM2-8B-Polish-Q6_K.gguf?download=true) |
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| **Q4_K_M** | ~4.8 GB | Najlepszy balans szybkości i inteligencji | [Pobierz Q4](https://huggingface.co/Michal1981/Liquid-LFM2-8B-Polish-Warrior/resolve/main/Liquid-LFM2-8B-Polish-Q4_K_M.gguf?download=true) |
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| **BF16** | ~15.5 GB | Pełna precyzja (do dalszego treningu) | [Pobierz F16](https://huggingface.co/Michal1981/Liquid-LFM2-8B-Polish-Warrior/resolve/main/Liquid-LFM2-8B-Polish-F16.gguf?download=true) |
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---
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> [!IMPORTANT]
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> **[English Version]** | **[Polska Wersja Poniżej]**
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## 🇺🇸 English Description
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**Liquid-LFM2-8B-Polish-Warrior** is the first specialized Polish adaptation of the innovative **Liquid LFM2 8B (A1B)** architecture. This model was meticulously fine-tuned by **Michal1981 (Warrior of Silicon)** to excel in Polish language understanding, with a strong focus on technical contexts, electronics, and programming (specifically C# and Arduino/EMS).
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### 📊 Training Progress (Final Results)
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The model reached its peak performance (**Sweet Spot**) at step **2800**, demonstrating an ideal balance between knowledge retention and linguistic flexibility.
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| Step | Training Loss | Validation Loss | Status |
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| :--- | :--- | :--- | :--- |
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| 200 | 1.4674 | 1.4427 | Initialization |
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| 1400 | 1.2975 | 1.3431 | Breakthrough |
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| **2800** | **0.9594** | **1.3356** | 👑 **Sweet Spot** |
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---
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## 🇵🇱 Polska Wersja
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**Liquid-LFM2-8B-Polish-Warrior** to pierwsza polska adaptacja architektury **Liquid LFM2 8B (A1B)**. Model został wytrenowany przez **Michala1981 (Wojownika Krzemu)**, aby zapewnić najwyższą jakość obsługi języka polskiego, ze szczególnym uwzględnieniem żargonu technicznego, elektroniki oraz programowania (C#, Arduino, EMS).
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### ⚔️ Filozofia Projektu
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Model powstał w duchu "Hattori Hanzo" – kucia cyfrowych ostrzy zdolnych stawić czoła bogom. W moim języku nie istnieje słowo "nie da się". Jest tylko "trudniej wykonalne i zajmie więcej czasu".
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### 📈 Charakterystyka Treningu
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Najlepszą formę model osiągnął w kroku **2800**, wykazując się doskonałym zrozumieniem polskiej fleksji przy najniższym błędzie walidacji (**1.3356**).
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---
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## 👨💻 Creator & Credits
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* **User/Creator**: Michal1981 (Hattori Hanzo)
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* **Architecture**: Liquid AI (LFM2-8B-A1B)
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* **Motto**: *Qapla'! Success is a journey, not a destination.*
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chat_template.jinja
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chat_template.jinja
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{{- bos_token -}}{%- set system_prompt = "" -%}{%- set ns = namespace(system_prompt="") -%}{%- if messages[0]["role"] == "system" -%} {%- set ns.system_prompt = messages[0]["content"] -%} {%- set messages = messages[1:] -%}{%- endif -%}{%- if tools -%} {%- set ns.system_prompt = ns.system_prompt + ("
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" if ns.system_prompt else "") + "List of tools: <|tool_list_start|>[" -%} {%- for tool in tools -%} {%- if tool is not string -%} {%- set tool = tool | tojson -%} {%- endif -%} {%- set ns.system_prompt = ns.system_prompt + tool -%} {%- if not loop.last -%} {%- set ns.system_prompt = ns.system_prompt + ", " -%} {%- endif -%} {%- endfor -%} {%- set ns.system_prompt = ns.system_prompt + "]<|tool_list_end|>" -%}{%- endif -%}{%- if ns.system_prompt -%} {{- "<|im_start|>system
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" + ns.system_prompt + "<|im_end|>
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" -}}{%- endif -%}{%- for message in messages -%} {{- "<|im_start|>" + message["role"] + "
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" -}} {%- set content = message["content"] -%} {%- if content is not string -%} {%- set content = content | tojson -%} {%- endif -%} {%- if message["role"] == "tool" -%} {%- set content = "<|tool_response_start|>" + content + "<|tool_response_end|>" -%} {%- endif -%} {{- content + "<|im_end|>
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" -}}{%- endfor -%}{%- if add_generation_prompt -%} {{- "<|im_start|>assistant
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" -}}{%- endif -%}
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config.json
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config.json
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{
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"architectures": [
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"Lfm2MoeForCausalLM"
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],
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"bos_token_id": 1,
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"conv_L_cache": 3,
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"conv_bias": false,
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"dtype": "bfloat16",
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"eos_token_id": 7,
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"hidden_size": 2048,
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"intermediate_size": 7168,
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"layer_types": [
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"conv",
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"conv",
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"full_attention",
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"conv",
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"conv",
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"conv",
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"full_attention",
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"conv",
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"conv",
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"conv",
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"full_attention",
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"conv",
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"conv",
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"conv",
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"full_attention",
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"conv",
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"conv",
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"conv",
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"full_attention",
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"conv",
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"conv",
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"full_attention",
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"conv",
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"conv"
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],
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"max_position_embeddings": 128000,
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"model_type": "lfm2_moe",
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"moe_intermediate_size": 1792,
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"norm_eps": 1e-05,
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"norm_topk_prob": true,
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"num_attention_heads": 32,
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"num_dense_layers": 2,
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"num_experts": 32,
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"num_experts_per_tok": 4,
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"num_hidden_layers": 24,
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"num_key_value_heads": 8,
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"pad_token_id": 0,
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"rope_theta": 1000000.0,
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"routed_scaling_factor": 1.0,
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"transformers_version": "4.57.0.dev0",
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"use_cache": true,
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"use_expert_bias": true,
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"vocab_size": 65536
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": 7,
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"pad_token_id": 0,
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"transformers_version": "4.57.0.dev0"
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}
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model-00001-of-00004.safetensors
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model-00001-of-00004.safetensors
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model-00002-of-00004.safetensors
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model-00002-of-00004.safetensors
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model.safetensors.index.json
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special_tokens_map.json
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special_tokens_map.json
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{
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"bos_token": {
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"content": "<|startoftext|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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"single_word": false
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},
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"eos_token": {
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"content": "<|im_end|>",
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"lstrip": false,
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"normalized": false,
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"rstrip": false,
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},
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"pad_token": {
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"content": "<|pad|>",
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"lstrip": false,
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"rstrip": false,
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"single_word": false
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}
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}
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tokenizer_config.json
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tokenizer_config.json
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