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Model: mrshu/mistral-sk-7b-alpaca-slovak-it
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: apache-2.0
+language:
+- sk
+- en
+base_model:
+- slovak-nlp/mistral-sk-7b
+datasets:
+- saillab/alpaca-slovak-cleaned
+tags:
+- slovak
+- instruction-tuned
+- mistral
+- lora
+- merged-lora
+- text-generation
+pipeline_tag: text-generation
+---
+
+# Mistral-sk-7B Alpaca Slovak IT
+
+Mistral-sk-7B Alpaca Slovak IT is an instruction-tuned Slovak assistant model
+derived from `slovak-nlp/mistral-sk-7b`. 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`.
+
+This is the compact 7B release candidate. It is intended for Slovak assistant
+experiments where lower memory use is more important than using the strongest
+available model in this release set.
+
+## 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 weaker than in larger models. 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/mistral-sk-7b` |
+| Base revision | `089497ae0d72018e9591895c54f774bf0b4a83a4` |
+| Release repository | [`mrshu/mistral-sk-7b-alpaca-slovak-it`](https://huggingface.co/mrshu/mistral-sk-7b-alpaca-slovak-it) |
+| Architecture | Mistral 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 | `2` |
+| Gradient accumulation | `8` |
+| 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 with a Mistral chat template in
+the tokenizer.
+
+## Usage
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_id = "mrshu/mistral-sk-7b-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=0.7,
+    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 strongly biased toward Slovak responses. Explicit English-only
+  or strict-format requests may not be followed reliably.
+- 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.