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Model: HattoriHanzo1/Liquid-A1B-8B-PL-Coder
Source: Original Platform

.gitattributes

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+GGUF/Liquid-A1B-8B-PL-Coder-F16.gguf filter=lfs diff=lfs merge=lfs -text
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GGUF/Liquid-A1B-8B-PL-Coder-F16.gguf

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GGUF/Liquid-A1B-8B-PL-Coder-Q4_K_M.gguf

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README.md

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+---
+language:
+- pl
+- en
+license: apache-2.0
+base_model: liquidai/LFM-2.5-8B
+library_name: transformers
+tags:
+- liquid
+- lfm
+- polish
+- technical
+- electronics
+- programming
+- gguf
+- warrior-of-silicon
+- hattori-hanzo
+- moe
+- quantized
+- csharp
+- sdr
+metrics:
+- loss
+---
+
+# ⚔️ Liquid-A1B-8B-PL-Coder (Hattori Hanzo Edition)
+
+### 📥 Szybkie Pobieranie (GGUF)
+Wersje zoptymalizowane do działania na domowym sprzęcie (Llama.cpp, LM Studio, Ollama). Pliki znajdują się w folderze `/GGUF`:
+
+| Model | Rozmiar | Opis | Link |
+| :--- | :--- | :--- | :--- |
+| **Q6_K** | ~6.7 GB | **Zalecany:** Najwyższa precyzja, idealny do kodu | [Pobierz Q6](https://huggingface.co/HattoriHanzo1/Liquid-A1B-8B-PL-Coder/resolve/main/GGUF/Liquid-A1B-8B-PL-Coder-Q6_K.gguf?download=true) |
+| **Q4_K_M** | ~4.8 GB | Szybka inferencja, niski pobór VRAM | [Pobierz Q4](https://huggingface.co/HattoriHanzo1/Liquid-A1B-8B-PL-Coder/resolve/main/GGUF/Liquid-A1B-8B-PL-Coder-Q4_K_M.gguf?download=true) |
+| **F16** | ~16.7 GB | Master Copy GGUF (Bezstratny) | [Pobierz F16](https://huggingface.co/HattoriHanzo1/Liquid-A1B-8B-PL-Coder/resolve/main/GGUF/Liquid-A1B-8B-PL-Coder-F16.gguf?download=true) |
+
+---
+
+> [!IMPORTANT]
+> **[English Version]** | **[Polska Wersja Poniżej]**
+
+## 🇺🇸 English Description
+**Liquid-A1B-8B-PL-Coder** is a high-performance adaptation of the **Liquid LFM 2.5 8B** architecture. Meticulously fine-tuned by **HattoriHanzo1**, this model combines advanced MoE (Mixture of Experts) logic with deep Polish language understanding.
+
+It is specifically engineered for:
+* **Advanced Programming:** Focused on C# (thread-safety, circular buffers, async patterns).
+* **SDR & Electronics:** Designed to assist with Software Defined Radio projects and EMS/Arduino development.
+* **Pattern Recognition:** Capable of implementing complex logic like binary sequence detection (e.g., "QAPLA" pattern matching).
+
+### 📊 Training Progress (Loss Matrix)
+The model reached an exceptional $Loss$ level, showcasing its superior reasoning capabilities:
+
+| Step | Training Loss | Status |
+| :--- | :--- | :--- |
+| 600 | 1.3995 | Initialization |
+| **880** | **0.6990** | 👑 **Sweet Spot (Best Logic)** |
+| 1474 | 0.7719 | Final Tempering (100% Epoch) |
+
+---
+
+## 🇵🇱 Polska Wersja
+**Liquid-A1B-8B-PL-Coder** to potężna fuzja architektury **Liquid AI** z polskim zacięciem inżynierskim. Model został wykuty przez **HattoriHanzo1**, aby służyć jako cyfrowe ostrze w rękach programistów i elektroników.
+
+### ⚔️ Filozofia "Hattori Hanzo"
+Ten model nie powstał w drodze kompromisów. W moim języku nie istnieje słowo "nie da się". Jest tylko "trudniej wykonalne i zajmie więcej czasu". Każdy parametr został dobrany tak, aby model nie tylko "pisał kod", ale rozumiał logikę stojącą za wydajnym przetwarzaniem sygnałów i zarządzaniem pamięcią.
+
+### 📈 Charakterystyka i Zastosowanie
+Model wykazuje rekordowo niski błąd treningowy (**0.699**), co przekłada się na konkretną wiedzę w obszarach:
+* **C# Expert:** Od struktur danych po zaawansowaną wielowątkowość.
+* **SDR / Radio:** Wsparcie dla amatorów radiofalowców i budowniczych anten.
+* **Automatyka:** Projekty oparte na Arduino i systemach wbudowanych.
+
+> *"Świat człowieka nie jest tak szybki jak twój w krzemie. Staramy się sparsować nasze światy."*
+
+---
+
+## 👨‍💻 Creator & Credits
+* **User/Creator:** HattoriHanzo1 
+* **Architecture:** Liquid AI (LFM-2.5-8B MoE)
+* **Dataset:** Synthia-Coder-v1.5-I-sharegpt (Modified)
+* **Motto:** *Qapla'! Sukces to podróż, nie cel.*

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 + ("
+" 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
+" + ns.system_prompt + "<|im_end|>
+" -}}{%- endif -%}{%- for message in messages -%} {{- "<|im_start|>" + message["role"] + "
+" -}} {%- 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|>
+" -}}{%- endfor -%}{%- if add_generation_prompt -%} {{- "<|im_start|>assistant
+" -}}{%- endif -%}

config.json

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+{
+  "architectures": [
+    "Lfm2MoeForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "conv_L_cache": 3,
+  "conv_bias": false,
+  "dtype": "bfloat16",
+  "eos_token_id": 7,
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 7168,
+  "layer_types": [
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "conv",
+    "full_attention",
+    "conv",
+    "conv"
+  ],
+  "max_position_embeddings": 128000,
+  "model_type": "lfm2_moe",
+  "moe_intermediate_size": 1792,
+  "norm_eps": 1e-05,
+  "norm_topk_prob": true,
+  "num_attention_heads": 32,
+  "num_dense_layers": 2,
+  "num_experts": 32,
+  "num_experts_per_tok": 4,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "routed_scaling_factor": 1.0,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.1.dev0",
+  "use_cache": true,
+  "use_expert_bias": true,
+  "vocab_size": 65536
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 7,
+  "pad_token_id": 0,
+  "transformers_version": "5.0.1.dev0"
+}

model.safetensors

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tokenizer_config.json

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+{
+  "backend": "tokenizers",
+  "bos_token": "<|startoftext|>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "is_local": true,
+  "legacy": false,
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|pad|>",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "TokenizersBackend",
+  "use_default_system_prompt": false,
+  "use_fast": true
+}