commit d08242016e2eb3a1a250aa854daa98ad042f7ee0
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Thu Oct 15 19:12:21 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: GaMS-Beta/GaMS-9B-SFT-Translator-DPO
    Source: Original Platform

diff --git a/.gitattributes b/.gitattributes
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diff --git a/README.md b/README.md
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+---
+license: gemma
+language:
+- sl
+- en
+- hr
+- sr
+- bs
+base_model:
+- GaMS-Beta/GaMS-9B-SFT-Translator
+pipeline_tag: text-generation
+---
+
+# Model Card for GaMS-DPO-Translator
+
+GaMS-Beta/GaMS-9B-SFT-Translator-DPO is a fine-tuned version of GaMS-9B-SFT-Translator. Direct Preference Optimization (DPO) was performed on the original model. The learning dataset was synthetially generated by using GaMS-9B-SFT-Translator and EuroLLM-9B-Instruct. 
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/652d40a78fa1fbb0aae165bb/94gX0PG8zRB_Zg31K2y_i.png)
+
+## Basic information
+
+- **Developed by:** team of researchers at the University of Ljubljana, Faculty for Computer and Information Science. Team members: Dario Vajda, Domen Vreš and Marko Robnik-Šikonja.
+- **Languages:** Slovene, English (primary), Croatian, Bosnian and Serbian (secondary). The model might also work for other languages supported by Gemma 2, even though it was not continually pretrained on them.
+- **Base model:** [cjvt/GaMS-9B-Instruct](https://huggingface.co/cjvt/GaMS-9B-Instruct)
+- **License:** [Gemma](https://ai.google.dev/gemma/terms)
+
+## Usage
+
+The model can be run through `pipeline` API using the following code:
+
+```python
+from transformers import pipeline
+
+model_id = "GaMS-Beta/GaMS-9B-SFT-Translator-DPO"
+
+pline = pipeline(
+    "text-generation",
+    model=model_id,
+    device_map="cuda" # replace with "mps" to run on a Mac device
+)
+
+# Example of response generation
+message = [{"role": "user", "content": "Prevedi naslednje angleško besedilo v slovenščino.\nToday is a nice day."}]
+response = pline(message, max_new_tokens=512)
+print("Translation:", response[0]["generated_text"][-1]["content"])
+```
+
+For multi GPU inference set the `device_map` to `auto`:
+
+```python
+from transformers import pipeline
+
+model_id = "GaMS-Beta/GaMS-9B-SFT-Translator-DPO"
+
+pline = pipeline(
+    "text-generation",
+    model=model_id,
+    device_map="auto"
+)
+
+# Example of response generation
+message = [{"role": "user", "content": "Prevedi naslednje angleško besedilo v slovenščino.\nToday is a nice day."}]
+response = pline(message, max_new_tokens=512)
+print("Model's response:", response[0]["generated_text"][-1]["content"])
+
+# Example of conversation chain
+new_message = response[0]["generated_text"]
+new_message.append({"role": "user", "content": "Lahko bolj podrobno opišeš ta dogodek?"})
+response = pline(new_message, max_new_tokens=1024)
+print("Model's response:", response[0]["generated_text"][-1]["content"])
+```
+
+## Data
+
+Data for fine-tuning the original model was acquired by translating a large corpora of wikipedia articles, ccnews articles, bookcorpus texts and english conversational datasets by two models(GaMS-9B-SFT-Translator and EuroLLM-9B-Instruct) which were then ranked by some automatic metrics for translation quality and reliability.
+
+## Training
+
+The model was trained on the [Vega HPC](https://izum.si/vega_slv/)
+
+## Evaluation
+
+The model was evaluated by our custom script on three types of data. The results are show in the following table.
+
+| Model | Overall Comet | ccnews | nemotron | wikipedia | Bad Lang (%) | Short (%) | Bad Markdown (%) |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| gemini-2.5-flash | 0.717982 | 0.702981 | 0.697498 | 0.753924 | 0.35% | 0.42% | 3.70% |
+| GaMS-9B-Instruct-DPO-Translator | 0.714729 | 0.708317 | 0.689316 | 0.746768 | 1.88% | 1.56% | 13.22% |
+| **GaMS-9B-SFT-Translator-DPO** | **0.708042** | **0.702903** | **0.679462** | **0.742583** | **0.91%** | **0.28%** | **18.28%** |
+| GaMS-27B-Instruct | 0.701284 | 0.686480 | 0.680014 | 0.730733 | 27.28% | 5.36% | 62.07% |
+| GaMS-9B-Instruct | 0.693659 | 0.685006 | 0.673394 | 0.723470 | 13.50% | 4.83% | 33.15% |
+| EuroLLM-9B-Instruct | 0.689321 | 0.668084 | 0.670723 | 0.729227 | 8.97% | 1.89% | 35.08% |
+| GaMS-9B-SFT-Translator | 0.682467 | 0.676580 | 0.673650 | 0.699602 | 5.14% | 1.48% | 30.53% |
+
+
+*Note* - the evaluation script and evaluation data can be found in this [github repo](https://github.com/DarioVajda/translation_dpo) under the data_pipeline folder. See the README for more detailed instructions.
+
+
+## Citation
+If you found this project useful in your work, please cite our paper with the following BibTeX citation:
+```txt
+@misc{vajda2025improvingllmsmachinetranslation,
+      title={Improving LLMs for Machine Translation Using Synthetic Preference Data}, 
+      author={Dario Vajda and Domen Vreš and Marko Robnik-Šikonja},
+      year={2025},
+      eprint={2508.14951},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2508.14951}, 
+}
+```
diff --git a/chat_template.jinja b/chat_template.jinja
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--- /dev/null
+++ b/chat_template.jinja
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+{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '
+' + message['content'] | trim + '<end_of_turn>
+' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model
+'}}{% endif %}
\ No newline at end of file
diff --git a/config.json b/config.json
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--- /dev/null
+++ b/config.json
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+{
+  "architectures": [
+    "Gemma2ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": 50.0,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "dtype": "bfloat16",
+  "eos_token_id": 1,
+  "final_logit_softcapping": 30.0,
+  "head_dim": 256,
+  "hidden_act": "gelu_pytorch_tanh",
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 3584,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "layer_types": [
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "full_attention",
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+    "full_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "full_attention",
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+    "full_attention",
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+    "full_attention",
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+    "full_attention",
+    "sliding_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 8192,
+  "model_type": "gemma2",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 42,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "sliding_window_size": 4096,
+  "transformers_version": "4.56.1",
+  "use_cache": true,
+  "vocab_size": 256000
+}
diff --git a/generation_config.json b/generation_config.json
new file mode 100644
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--- /dev/null
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+{
+  "_from_model_config": true,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "do_sample": true,
+  "eos_token_id": 1,
+  "pad_token_id": 0,
+  "transformers_version": "4.56.1"
+}
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