From 512b3411f4c9d4d4f67a9883b8a6e3b3f38a32a9 Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Fri, 24 Jul 2026 08:18:10 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: OpenLLM-Ro/RoGemma-7b-Instruct Source: Original Platform --- .gitattributes | 36 + README.md | 699 ++++++++++++ config.json | 29 + generation_config.json | 7 + model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 261 +++++ scheduler.pt | 3 + special_tokens_map.json | 34 + tokenizer.json | 3 + tokenizer.model | 3 + tokenizer_config.json | 1759 ++++++++++++++++++++++++++++++ 14 files changed, 2846 insertions(+) create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 config.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 scheduler.pt create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer.model create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..32694d0 --- /dev/null +++ b/README.md @@ -0,0 +1,699 @@ +--- +license: cc-by-nc-4.0 +language: +- ro +base_model: +- google/gemma-7b +datasets: +- OpenLLM-Ro/ro_sft_alpaca +- OpenLLM-Ro/ro_sft_alpaca_gpt4 +- OpenLLM-Ro/ro_sft_dolly +- OpenLLM-Ro/ro_sft_selfinstruct_gpt4 +- OpenLLM-Ro/ro_sft_norobots +- OpenLLM-Ro/ro_sft_orca +- OpenLLM-Ro/ro_sft_camel +- OpenLLM-Ro/ro_sft_oasst +- OpenLLM-Ro/ro_sft_ultrachat +- OpenLLM-Ro/ro_sft_magpie_mt +- OpenLLM-Ro/ro_sft_magpie_reasoning +model-index: + - name: OpenLLM-Ro/RoGemma-7b-Instruct-2025-04-23 + results: + - task: + type: text-generation + dataset: + name: RoMT-Bench + type: RoMT-Bench + metrics: + - name: Score + type: Score + value: 6.28 + - task: + type: text-generation + dataset: + name: RoCulturaBench + type: RoCulturaBench + metrics: + - name: Score + type: Score + value: 3.65 + - task: + type: text-generation + dataset: + name: Romanian_Academic_Benchmarks + type: Romanian_Academic_Benchmarks + metrics: + - name: Average accuracy + type: accuracy + value: 50.52 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_arc_challenge + type: OpenLLM-Ro/ro_arc_challenge + metrics: + - name: Average accuracy + type: accuracy + value: 47.70 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_mmlu + type: OpenLLM-Ro/ro_mmlu + metrics: + - name: Average accuracy + type: accuracy + value: 51.66 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_winogrande + type: OpenLLM-Ro/ro_winogrande + metrics: + - name: Average accuracy + type: accuracy + value: 66.32 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_hellaswag + type: OpenLLM-Ro/ro_hellaswag + metrics: + - name: Average accuracy + type: accuracy + value: 53.59 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_gsm8k + type: OpenLLM-Ro/ro_gsm8k + metrics: + - name: Average accuracy + type: accuracy + value: 36.04 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_truthfulqa + type: OpenLLM-Ro/ro_truthfulqa + metrics: + - name: Average accuracy + type: accuracy + value: 47.81 + - task: + type: text-generation + dataset: + name: LaRoSeDa_binary + type: LaRoSeDa_binary + metrics: + - name: Average macro-f1 + type: macro-f1 + value: 95.44 + - task: + type: text-generation + dataset: + name: LaRoSeDa_multiclass + type: LaRoSeDa_multiclass + metrics: + - name: Average macro-f1 + type: macro-f1 + value: 59.24 + - task: + type: text-generation + dataset: + name: WMT_EN-RO + type: WMT_EN-RO + metrics: + - name: Average bleu + type: bleu + value: 25.17 + - task: + type: text-generation + dataset: + name: WMT_RO-EN + type: WMT_RO-EN + metrics: + - name: Average bleu + type: bleu + value: 21.17 + - task: + type: text-generation + dataset: + name: XQuAD + type: XQuAD + metrics: + - name: Average exact_match + type: exact_match + value: 15.88 + - task: + type: text-generation + dataset: + name: XQuAD + type: XQuAD + metrics: + - name: Average f1 + type: f1 + value: 29.16 + - task: + type: text-generation + dataset: + name: STS + type: STS + metrics: + - name: Average spearman + type: spearman + value: 75.90 + - task: + type: text-generation + dataset: + name: STS + type: STS + metrics: + - name: Average pearson + type: pearson + value: 75.16 + - task: + type: text-generation + dataset: + name: RoMT-Bench + type: RoMT-Bench + metrics: + - name: First turn + type: Score + value: 6.97 + - name: Second turn + type: Score + value: 5.58 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_arc_challenge + type: OpenLLM-Ro/ro_arc_challenge + metrics: + - name: 0-shot + type: accuracy + value: 46.19 + - name: 1-shot + type: accuracy + value: 46.53 + - name: 3-shot + type: accuracy + value: 46.02 + - name: 5-shot + type: accuracy + value: 48.33 + - name: 10-shot + type: accuracy + value: 49.27 + - name: 25-shot + type: accuracy + value: 49.87 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_mmlu + type: OpenLLM-Ro/ro_mmlu + metrics: + - name: 0-shot + type: accuracy + value: 51.13 + - name: 1-shot + type: accuracy + value: 50.94 + - name: 3-shot + type: accuracy + value: 52.67 + - name: 5-shot + type: accuracy + value: 51.90 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_winogrande + type: OpenLLM-Ro/ro_winogrande + metrics: + - name: 0-shot + type: accuracy + value: 67.40 + - name: 1-shot + type: accuracy + value: 65.04 + - name: 3-shot + type: accuracy + value: 65.67 + - name: 5-shot + type: accuracy + value: 67.17 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_hellaswag + type: OpenLLM-Ro/ro_hellaswag + metrics: + - name: 0-shot + type: accuracy + value: 58.03 + - name: 1-shot + type: accuracy + value: 56.63 + - name: 3-shot + type: accuracy + value: 52.47 + - name: 5-shot + type: accuracy + value: 48.63 + - name: 10-shot + type: accuracy + value: 52.18 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_gsm8k + type: OpenLLM-Ro/ro_gsm8k + metrics: + - name: 1-shot + type: accuracy + value: 24.11 + - name: 3-shot + type: accuracy + value: 37.76 + - name: 5-shot + type: accuracy + value: 46.25 + - task: + type: text-generation + dataset: + name: LaRoSeDa_binary + type: LaRoSeDa_binary + metrics: + - name: 0-shot + type: macro-f1 + value: 96.33 + - name: 1-shot + type: macro-f1 + value: 94.62 + - name: 3-shot + type: macro-f1 + value: 95.06 + - name: 5-shot + type: macro-f1 + value: 95.76 + - task: + type: text-generation + dataset: + name: LaRoSeDa_multiclass + type: LaRoSeDa_multiclass + metrics: + - name: 0-shot + type: macro-f1 + value: 43.65 + - name: 1-shot + type: macro-f1 + value: 64.30 + - name: 3-shot + type: macro-f1 + value: 64.22 + - name: 5-shot + type: macro-f1 + value: 64.81 + - task: + type: text-generation + dataset: + name: WMT_EN-RO + type: WMT_EN-RO + metrics: + - name: 0-shot + type: bleu + value: 13.30 + - name: 1-shot + type: bleu + value: 28.59 + - name: 3-shot + type: bleu + value: 29.48 + - name: 5-shot + type: bleu + value: 29.31 + - task: + type: text-generation + dataset: + name: WMT_RO-EN + type: WMT_RO-EN + metrics: + - name: 0-shot + type: bleu + value: 1.11 + - name: 1-shot + type: bleu + value: 18.97 + - name: 3-shot + type: bleu + value: 31.99 + - name: 5-shot + type: bleu + value: 32.60 + - task: + type: text-generation + dataset: + name: XQuAD_EM + type: XQuAD_EM + metrics: + - name: 0-shot + type: exact_match + value: 17.31 + - name: 1-shot + type: exact_match + value: 12.44 + - name: 3-shot + type: exact_match + value: 13.11 + - name: 5-shot + type: exact_match + value: 20.67 + - task: + type: text-generation + dataset: + name: XQuAD_F1 + type: XQuAD_F1 + metrics: + - name: 0-shot + type: f1 + value: 29.90 + - name: 1-shot + type: f1 + value: 24.24 + - name: 3-shot + type: f1 + value: 25.64 + - name: 5-shot + type: f1 + value: 36.86 + - task: + type: text-generation + dataset: + name: STS_Spearman + type: STS_Spearman + metrics: + - name: 1-shot + type: spearman + value: 76.50 + - name: 3-shot + type: spearman + value: 73.63 + - name: 5-shot + type: spearman + value: 77.58 + - task: + type: text-generation + dataset: + name: STS_Pearson + type: STS_Pearson + metrics: + - name: 1-shot + type: pearson + value: 75.15 + - name: 3-shot + type: pearson + value: 72.69 + - name: 5-shot + type: pearson + value: 77.63 + +--- + +# Model Card for Model ID + +This model points/is identical to [RoGemma-7b-Instruct-2025-04-23](https://huggingface.co/OpenLLM-Ro/RoGemma-7b-Instruct-2025-04-23). + + + +RoGemma is a family of pretrained and fine-tuned generative text models for Romanian. This is the repository for the **instruct 7B model**. Links to other models can be found at the bottom of this page. + +## Model Details + +### Model Description + + +OpenLLM-Ro represents the first open-source effort to build a LLM specialized for Romanian. OpenLLM-Ro developed and publicly releases a collection of Romanian LLMs, both in the form of foundational model and instruct and chat variants. + + +- **Developed by:** OpenLLM-Ro + + + +- **Language(s):** Romanian +- **License:** cc-by-nc-4.0 +- **Finetuned from model:** [gemma-7b](https://huggingface.co/google/gemma-7b) +- **Trained using:** [RoAlpaca](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_alpaca), [RoAlpacaGPT4](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_alpaca_gpt4), [RoDolly](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_dolly), [RoSelfInstruct](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_selfinstruct_gpt4), [RoNoRobots](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_norobots), [RoOrca](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_orca), [RoCamel](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_camel), [RoOpenAssistant](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_oasst), [RoUltraChat](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_ultrachat), [RoMagpiePro](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_magpie_mt), [RoMagpieReasoning](https://huggingface.co/datasets/OpenLLM-Ro/ro_sft_magpie_reasoning) + + +### Model Sources + + + +- **Repository:** https://github.com/OpenLLM-Ro/LLaMA-Factory +- **Paper:** https://arxiv.org/abs/2406.18266 + +## Intended Use + +### Intended Use Cases + +RoGemma is intented for research use in Romanian. Base models can be adapted for a variety of natural language tasks while instruction and chat tuned models are intended for assistant-like chat. + +### Out-of-Scope Use + + + +Use in any manner that violates the license, any applicable laws or regluations, use in languages other than Romanian. + + + +## How to Get Started with the Model + +Use the code below to get started with the model. + +```python +from transformers import AutoTokenizer, AutoModelForCausalLM + +tokenizer = AutoTokenizer.from_pretrained("OpenLLM-Ro/RoGemma-7b-Instruct") +model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoGemma-7b-Instruct") + +instruction = "Ce jocuri de societate pot juca cu prietenii mei?" +chat = [ + {"role": "user", "content": instruction}, + ] +prompt = tokenizer.apply_chat_template(chat, tokenize=False, system_message="") + +inputs = tokenizer.encode(prompt, add_special_tokens=False, return_tensors="pt") +outputs = model.generate(input_ids=inputs, max_new_tokens=128) +print(tokenizer.decode(outputs[0])) +``` + +## Academic Benchmarks + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Model
Average
ARC
MMLU
Winogrande
Hellaswag
GSM8k
TruthfulQA
gemma-1.1-7b-it
41.44
40.32
47.22
55.01
47.03
9.50
49.58
RoGemma-7b-Instruct-2024-06-28
53.41
52.44
54.44
69.36
61.96
31.06
51.23
RoGemma-7b-Instruct-2024-10-09
50.48
52.01
52.37
66.97
56.34
25.98
49.18
RoGemma-7b-Instruct-2025-04-23
50.52
47.70
51.66
66.32
53.59
36.04
47.81
RoGemma-7b-Instruct-DPO-2024-10-09
48.27
46.66
54.45
63.73
49.33
34.98
40.45
+ +## Downstream tasks + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
LaRoSeDa
WMT
Few-shot
Finetuned
Few-shot
Finetuned
Model
Binary
(Macro F1)
Multiclass
(Macro F1)
Binary
(Macro F1)
Multiclass
(Macro F1)
EN-RO
(Bleu)
RO-EN
(Bleu)
EN-RO
(Bleu)
RO-EN
(Bleu)
+
gemma-1.1-7b-it
87.54
51.48
83.87
85.61
17.96
27.74
25.48
36.11
RoGemma-7b-Instruct-2024-06-28
97.86
65.70
98.43
87.17
27.91
23.08
27.99
39.51
RoGemma-7b-Instruct-2024-10-09
86.96
56.72
98.80
85.81
24.45
14.20
25.96
39.07
RoGemma-7b-Instruct-2025-04-23
95.44
59.24
-
-
25.17
21.17
-
-
RoGemma-7b-Instruct-DPO-2024-10-09
96.45
63.23
-
-
20.73
7.87
-
-
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
XQuAD
STS
Few-shot
Finetuned
Few-shot
Finetuned
Model
(EM)
(F1)
(EM)
(F1)
(Spearman)
(Pearson)
(Spearman)
(Pearson)
gemma-1.1-7b-it
42.10
62.30
60.34
77.40
49.10
50.23
83.43
83.64
RoGemma-7b-Instruct-2024-06-28
17.75
28.11
52.02
68.43
73.96
75.16
86.45
86.31
RoGemma-7b-Instruct-2024-10-09
26.03
41.58
46.72
60.79
73.23
71.58
88.42
88.45
RoGemma-7b-Instruct-2025-04-23
15.88
29.16
-
-
75.90
75.16
-
-
RoGemma-7b-Instruct-DPO-2024-10-09
19.14
38.10
-
-
69.38
69.34
-
-
+ + +## MT-Bench + + + + + + + + + + + + + + + + + + + + + + + + + + +
Model
Average
1st turn
2nd turn
Answers in Ro
gemma-1.1-7b-it
4.83
5.11
4.55
160/160
RoGemma-7b-Instruct-2024-06-28
5.26
5.92
4.60
160/160
RoGemma-7b-Instruct-2024-10-09
5.24
5.55
4.94
160/160
RoGemma-7b-Instruct-2025-04-23
6.28
6.97
5.58
160/160
RoGemma-7b-Instruct-DPO-2024-10-09
5.47
5.92
5.03
160/160
+ +## RoCulturaBench + + + + + + + + + + + + + + + + + + + + + + + + +
Model
Average
Answers in Ro
gemma-1.1-7b-it
3.38
100/100
RoGemma-7b-Instruct-2024-06-28
3.26
100/100
RoGemma-7b-Instruct-2024-10-09
3.51
100/100
RoGemma-7b-Instruct-2025-04-23
3.65
100/100
RoGemma-7b-Instruct-DPO-2024-10-09
3.94
100/100
+ +## RoGemma Model Family + +| Model | Link | +|--------------------|:--------:| +|RoGemma-7b-Instruct-2024-06-28| [link](https://huggingface.co/OpenLLM-Ro/RoGemma-7b-Instruct-2024-06-28) | +|RoGemma-7b-Instruct-2024-10-09| [link](https://huggingface.co/OpenLLM-Ro/RoGemma-7b-Instruct-2024-10-09) | +|*RoGemma-7b-Instruct-2025-04-23*| [link](https://huggingface.co/OpenLLM-Ro/RoGemma-7b-Instruct-2025-04-23) | +|RoGemma-7b-Instruct-DPO-2024-10-09| [link](https://huggingface.co/OpenLLM-Ro/RoGemma-7b-Instruct-DPO-2024-10-09) | + + +## Citation + +``` +@inproceedings{masala-etal-2024-vorbesti, + title = "``Vorbe\c{s}ti Rom{\^a}ne\c{s}te?'' A Recipe to Train Powerful {R}omanian {LLM}s with {E}nglish Instructions", + author = "Masala, Mihai and Ilie-Ablachim, Denis and Dima, Alexandru and Corlatescu, Dragos Georgian and Zavelca, Miruna-Andreea and Olaru, Ovio and Terian, Simina-Maria and Terian, Andrei and Leordeanu, Marius and Velicu, Horia and Popescu, Marius and Dascalu, Mihai and Rebedea, Traian", + editor = "Al-Onaizan, Yaser and Bansal, Mohit and Chen, Yun-Nung", + booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024", + month = nov, + year = "2024", + address = "Miami, Florida, USA", + publisher = "Association for Computational Linguistics", + url = "https://aclanthology.org/2024.findings-emnlp.681/", + doi = "10.18653/v1/2024.findings-emnlp.681", + pages = "11632--11647" +} +``` + \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..32240dd --- /dev/null +++ b/config.json @@ -0,0 +1,29 @@ +{ + "_name_or_path": 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