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Model: mrshu/qwen3-14b-sk-alpaca-slovak-it
Source: Original Platform

.gitattributes

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README.md

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+---
+library_name: transformers
+license: apache-2.0
+language:
+- sk
+- en
+base_model:
+- slovak-nlp/Qwen3-14B-sk
+datasets:
+- saillab/alpaca-slovak-cleaned
+tags:
+- slovak
+- instruction-tuned
+- qwen3
+- lora
+- merged-lora
+- text-generation
+pipeline_tag: text-generation
+---
+
+# Qwen3-14B-sk Alpaca Slovak IT
+
+Qwen3-14B-sk Alpaca Slovak IT is an instruction-tuned Slovak assistant model
+derived from `slovak-nlp/Qwen3-14B-sk`. It was trained with a LoRA supervised
+fine-tuning recipe on Slovak Alpaca-style instruction data and then merged back
+into the base model, so the released artifact can be loaded directly with
+`transformers`.
+
+The model is designed to answer in Slovak by default while still attempting to
+follow explicit user requests for another language or a specific output format.
+
+## Intended Use
+
+This model is intended for Slovak instruction following, Slovak question
+answering, drafting, rewriting, summarization-style prompts, and general
+assistant workflows where Slovak is the primary language.
+
+It can also respond to English prompts and translation-style requests, but
+language control is not guaranteed. Use additional application-level checks for
+strict formatting, policy compliance, or high-reliability translation.
+
+Do not use this model as the sole source for medical, legal, financial, safety,
+or other high-stakes decisions. It has not been safety aligned, red-teamed, or
+moderated for production deployment.
+
+## Model Details
+
+| Field | Value |
+| --- | --- |
+| Base model | `slovak-nlp/Qwen3-14B-sk` |
+| Base revision | `61bc40572b2fa4720e75a7a9de457151aefce396` |
+| Release repository | [`mrshu/qwen3-14b-sk-alpaca-slovak-it`](https://huggingface.co/mrshu/qwen3-14b-sk-alpaca-slovak-it) |
+| Architecture | Qwen3 causal language model |
+| Tuned artifact | Merged full-weight checkpoint |
+| Adapter used during training | LoRA |
+| Weight dtype | bfloat16 |
+| License | Apache-2.0 |
+
+## Training Data
+
+The model was instruction-tuned on
+[`saillab/alpaca-slovak-cleaned`](https://huggingface.co/datasets/saillab/alpaca-slovak-cleaned),
+a Slovak Alpaca-style instruction dataset.
+
+Dataset preparation converted each example into a chat-style conversation with
+system, user, and assistant messages. Empty instruction/output examples were
+excluded, and duplicate instruction/input/output triples were removed across
+the prepared splits.
+
+| Split | Rows |
+| --- | ---: |
+| Train | 41,601 |
+| Held-out | 10,401 |
+
+The data preparation used dataset revision
+`058172466eb1d6a28b161f29c74350911d154161`.
+
+Each training conversation used this system prompt:
+
+```text
+Si užitočný asistent. Riaď sa jazykom a požadovaným formátom používateľa. Ak používateľ nežiada iný jazyk, odpovedaj po slovensky.
+```
+
+## Training Recipe
+
+The model was trained with supervised fine-tuning using PEFT LoRA. Only the
+assistant turns were included in the training loss.
+
+| Setting | Value |
+| --- | --- |
+| LoRA rank / alpha / dropout | `32` / `64` / `0.05` |
+| Target modules | linear projection modules |
+| Sequence length | `4096` |
+| Sample packing | enabled |
+| Epochs | `1` |
+| Effective batch size | `16` |
+| Micro batch size | `1` |
+| Gradient accumulation | `16` |
+| Learning rate | `1e-4` |
+| Scheduler | cosine |
+| Warmup ratio | `0.06` |
+| Optimizer | fused AdamW |
+| Precision | bfloat16 |
+| Gradient checkpointing | enabled |
+| Seed | `42` |
+
+After training, the LoRA adapter was merged into the base model with PEFT and
+saved as a standalone safetensors checkpoint.
+
+## Usage
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "mrshu/qwen3-14b-sk-alpaca-slovak-it"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True,
+)
+
+messages = [
+    {
+        "role": "system",
+        "content": (
+            "Si užitočný asistent. Riaď sa jazykom a požadovaným formátom "
+            "používateľa. Ak používateľ nežiada iný jazyk, odpovedaj po slovensky."
+        ),
+    },
+    {"role": "user", "content": "Stručne vysvetli, čo je LoRA."},
+]
+
+inputs = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt",
+).to(model.device)
+
+outputs = model.generate(
+    inputs,
+    max_new_tokens=512,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.95,
+)
+
+print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True))
+```
+
+## Limitations
+
+- The supervised fine-tuning data is translated instruction data, so the model
+  may inherit translation artifacts, unnatural phrasing, or source-dataset
+  biases.
+- The model is biased toward Slovak responses. Explicit requests for another
+  language may work, but they are not guaranteed.
+- Strict JSON, exact labels, citations, and other constrained formats should be
+  validated outside the model.
+- The model may hallucinate facts, produce unsafe content, or follow malicious
+  instructions without additional safeguards.

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 17408,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 40960,
+  "max_window_layers": 40,
+  "model_type": "qwen3",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "5.5.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.5.0"
+}

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