commit f760bdb35d3258271a80a8c311b99db9bd27a69c Author: ModelHub XC Date: Tue Aug 4 16:33:18 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: OpenLLM-Ro/RoLlama3.1-8b-Instruct-DPO Source: Original Platform 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..24b78eb --- /dev/null +++ b/README.md @@ -0,0 +1,701 @@ +--- +license: cc-by-nc-4.0 +language: +- ro +base_model: +- OpenLLM-Ro/RoLlama3.1-8b-Instruct-2025-04-23 +datasets: +- OpenLLM-Ro/ro_dpo_helpsteer +- OpenLLM-Ro/ro_dpo_ultrafeedback +- OpenLLM-Ro/ro_dpo_magpie +- OpenLLM-Ro/ro_dpo_argilla_magpie +- OpenLLM-Ro/ro_dpo_helpsteer2 +model-index: + - name: OpenLLM-Ro/RoLlama3.1-8b-Instruct-DPO-2025-04-23 + results: + - task: + type: text-generation + dataset: + name: RoMT-Bench + type: RoMT-Bench + metrics: + - name: Score + type: Score + value: 7.00 + - task: + type: text-generation + dataset: + name: RoCulturaBench + type: RoCulturaBench + metrics: + - name: Score + type: Score + value: 4.73 + - task: + type: text-generation + dataset: + name: Romanian_Academic_Benchmarks + type: Romanian_Academic_Benchmarks + metrics: + - name: Average accuracy + type: accuracy + value: 53.76 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_arc_challenge + type: OpenLLM-Ro/ro_arc_challenge + metrics: + - name: Average accuracy + type: accuracy + value: 51.09 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_mmlu + type: OpenLLM-Ro/ro_mmlu + metrics: + - name: Average accuracy + type: accuracy + value: 56.22 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_winogrande + type: OpenLLM-Ro/ro_winogrande + metrics: + - name: Average accuracy + type: accuracy + value: 66.77 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_hellaswag + type: OpenLLM-Ro/ro_hellaswag + metrics: + - name: Average accuracy + type: accuracy + value: 59.38 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_gsm8k + type: OpenLLM-Ro/ro_gsm8k + metrics: + - name: Average accuracy + type: accuracy + value: 31.54 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_truthfulqa + type: OpenLLM-Ro/ro_truthfulqa + metrics: + - name: Average accuracy + type: accuracy + value: 57.56 + - task: + type: text-generation + dataset: + name: LaRoSeDa_binary + type: LaRoSeDa_binary + metrics: + - name: Average macro-f1 + type: macro-f1 + value: 96.87 + - task: + type: text-generation + dataset: + name: LaRoSeDa_multiclass + type: LaRoSeDa_multiclass + metrics: + - name: Average macro-f1 + type: macro-f1 + value: 60.75 + - task: + type: text-generation + dataset: + name: WMT_EN-RO + type: WMT_EN-RO + metrics: + - name: Average bleu + type: bleu + value: 20.30 + - task: + type: text-generation + dataset: + name: WMT_RO-EN + type: WMT_RO-EN + metrics: + - name: Average bleu + type: bleu + value: 18.57 + - task: + type: text-generation + dataset: + name: XQuAD + type: XQuAD + metrics: + - name: Average exact_match + type: exact_match + value: 9.22 + - task: + type: text-generation + dataset: + name: XQuAD + type: XQuAD + metrics: + - name: Average f1 + type: f1 + value: 22.75 + - task: + type: text-generation + dataset: + name: STS + type: STS + metrics: + - name: Average spearman + type: spearman + value: 30.82 + - task: + type: text-generation + dataset: + name: STS + type: STS + metrics: + - name: Average pearson + type: pearson + value: 20.25 + - task: + type: text-generation + dataset: + name: RoMT-Bench + type: RoMT-Bench + metrics: + - name: First turn + type: Score + value: 7.30 + - name: Second turn + type: Score + value: 6.70 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_arc_challenge + type: OpenLLM-Ro/ro_arc_challenge + metrics: + - name: 0-shot + type: accuracy + value: 51.59 + - name: 1-shot + type: accuracy + value: 52.10 + - name: 3-shot + type: accuracy + value: 50.99 + - name: 5-shot + type: accuracy + value: 50.81 + - name: 10-shot + type: accuracy + value: 49.70 + - name: 25-shot + type: accuracy + value: 51.33 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_mmlu + type: OpenLLM-Ro/ro_mmlu + metrics: + - name: 0-shot + type: accuracy + value: 56.88 + - name: 1-shot + type: accuracy + value: 55.61 + - name: 3-shot + type: accuracy + value: 56.06 + - name: 5-shot + type: accuracy + value: 56.31 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_winogrande + type: OpenLLM-Ro/ro_winogrande + metrics: + - name: 0-shot + type: accuracy + value: 65.67 + - name: 1-shot + type: accuracy + value: 66.30 + - name: 3-shot + type: accuracy + value: 67.40 + - name: 5-shot + type: accuracy + value: 67.72 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_hellaswag + type: OpenLLM-Ro/ro_hellaswag + metrics: + - name: 0-shot + type: accuracy + value: 60.53 + - name: 1-shot + type: accuracy + value: 60.37 + - name: 3-shot + type: accuracy + value: 58.20 + - name: 5-shot + type: accuracy + value: 58.18 + - name: 10-shot + type: accuracy + value: 59.61 + - task: + type: text-generation + dataset: + name: OpenLLM-Ro/ro_gsm8k + type: OpenLLM-Ro/ro_gsm8k + metrics: + - name: 1-shot + type: accuracy + value: 25.09 + - name: 3-shot + type: accuracy + value: 30.02 + - name: 5-shot + type: accuracy + value: 39.50 + - task: + type: text-generation + dataset: + name: LaRoSeDa_binary + type: LaRoSeDa_binary + metrics: + - name: 0-shot + type: macro-f1 + value: 95.39 + - name: 1-shot + type: macro-f1 + value: 95.90 + - name: 3-shot + type: macro-f1 + value: 98.00 + - name: 5-shot + type: macro-f1 + value: 98.17 + - task: + type: text-generation + dataset: + name: LaRoSeDa_multiclass + type: LaRoSeDa_multiclass + metrics: + - name: 0-shot + type: macro-f1 + value: 60.30 + - name: 1-shot + type: macro-f1 + value: 64.73 + - name: 3-shot + type: macro-f1 + value: 58.69 + - name: 5-shot + type: macro-f1 + value: 59.30 + - task: + type: text-generation + dataset: + name: WMT_EN-RO + type: WMT_EN-RO + metrics: + - name: 0-shot + type: bleu + value: 5.46 + - name: 1-shot + type: bleu + value: 26.08 + - name: 3-shot + type: bleu + value: 25.90 + - name: 5-shot + type: bleu + value: 23.76 + - task: + type: text-generation + dataset: + name: WMT_RO-EN + type: WMT_RO-EN + metrics: + - name: 0-shot + type: bleu + value: 2.74 + - name: 1-shot + type: bleu + value: 20.95 + - name: 3-shot + type: bleu + value: 31.53 + - name: 5-shot + type: bleu + value: 19.05 + - task: + type: text-generation + dataset: + name: XQuAD_EM + type: XQuAD_EM + metrics: + - name: 0-shot + type: exact_match + value: 12.27 + - name: 1-shot + type: exact_match + value: 17.98 + - name: 3-shot + type: exact_match + value: 5.04 + - name: 5-shot + type: exact_match + value: 1.60 + - task: + type: text-generation + dataset: + name: XQuAD_F1 + type: XQuAD_F1 + metrics: + - name: 0-shot + type: f1 + value: 26.24 + - name: 1-shot + type: f1 + value: 32.54 + - name: 3-shot + type: f1 + value: 18.00 + - name: 5-shot + type: f1 + value: 14.22 + - task: + type: text-generation + dataset: + name: STS_Spearman + type: STS_Spearman + metrics: + - name: 1-shot + type: spearman + value: 76.70 + - name: 3-shot + type: spearman + value: 2.82 + - name: 5-shot + type: spearman + value: 12.95 + - task: + type: text-generation + dataset: + name: STS_Pearson + type: STS_Pearson + metrics: + - name: 1-shot + type: pearson + value: 77.30 + - name: 3-shot + type: pearson + value: -14.56 + - name: 5-shot + type: pearson + value: -1.99 + +--- + +# Model Card for Model ID + +*Built with Meta Llama 3.1* + +This model points/is identical to [RoLlama3.1-8b-Instruct-DPO-2025-04-23](https://huggingface.co/OpenLLM-Ro/RoLlama3.1-8b-Instruct-DPO-2025-04-23). + + + +RoLlama3.1 is a family of pretrained and fine-tuned generative text models for Romanian. This is the repository for the **human aligned instruct 8B 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:** [RoLlama3.1-8b-Instruct-2025-04-23](https://huggingface.co/OpenLLM-Ro/RoLlama3.1-8b-Instruct-2025-04-23) +- **Trained using:** [RoHelpSteer](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_helpsteer), [RoUltraFeedback](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_ultrafeedback), [RoMagpieDPO](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_magpie), [RoArgillaMagpie](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_argilla_magpie), [RoHelpSteer2](https://huggingface.co/datasets/OpenLLM-Ro/ro_dpo_helpsteer2) + +### Model Sources + + + +- **Repository:** https://github.com/OpenLLM-Ro/LLaMA-Factory +- **Paper:** https://arxiv.org/abs/2406.18266 + +## Intended Use + +### Intended Use Cases + +RoLlama3.1 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/RoLlama3.1-8b-Instruct-DPO") +model = AutoModelForCausalLM.from_pretrained("OpenLLM-Ro/RoLlama3.1-8b-Instruct-DPO") + +instruction = "Ce jocuri de societate pot juca cu prietenii mei?" +chat = [ + {"role": "system", "content": "Ești un asistent folositor, respectuos și onest. Încearcă să ajuți cât mai mult prin informațiile oferite, excluzând răspunsuri toxice, rasiste, sexiste, periculoase și ilegale."}, + {"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
Llama-3.1-8B-Instruct
49.87
42.86
53.73
59.71
56.82
35.56
50.54
RoLlama3.1-8b-Instruct-2024-10-09
53.03
47.69
54.57
65.84
59.94
44.30
45.82
RoLlama3.1-8b-Instruct-2025-04-23
53.36
48.97
55.17
66.52
60.73
42.03
46.71
RoLlama3.1-8b-Instruct-DPO-2024-10-09
52.74
44.84
55.06
65.87
58.67
44.17
47.82
RoLlama3.1-8b-Instruct-DPO-2025-04-23
53.76
51.09
56.22
66.77
59.38
31.54
57.56
+ + + +## 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)
+
Llama-3.1-8B-Instruct
95.74
59.49
98.57
82.41
19.01
27.77
29.02
39.80
RoLlama3.1-8b-Instruct-2024-10-09
94.56
60.10
95.12
87.53
21.88
23.99
28.27
40.44
RoLlama3.1-8b-Instruct-2025-04-23
95.32
60.84
-
-
23.18
25.11
-
-
RoLlama3.1-8b-Instruct-DPO-2024-10-09
96.10
55.37
-
-
21.29
21.86
-
-
RoLlama3.1-8b-Instruct-DPO-2025-04-23
96.87
60.75
-
-
20.30
18.57
-
-
+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
XQuAD
STS
Few-shot
Finetuned
Few-shot
Finetuned
Model
(EM)
(F1)
(EM)
(F1)
(Spearman)
(Pearson)
(Spearman)
(Pearson)
Llama-3.1-8B-Instruct
44.96
64.45
69.50
84.31
72.11
71.64
84.59
84.96
RoLlama3.1-8b-Instruct-2024-10-09
13.59
23.56
49.41
62.93
75.89
76.00
86.86
87.05
RoLlama3.1-8b-Instruct-2025-04-23
10.74
19.75
-
-
73.53
74.93
-
-
RoLlama3.1-8b-Instruct-DPO-2024-10-09
21.58
36.54
-
-
78.01
77.98
-
-
RoLlama3.1-8b-Instruct-DPO-2025-04-23
9.22
22.75
-
-
30.82
20.25
-
-
+ +## MT-Bench + + + + + + + + + + + + + + + + + + + + + + + + + + +
Model
Average
1st turn
2nd turn
Answers in Ro
Llama-3.1-8B-Instruct
5.69
5.85
5.53
160/160
RoLlama3.1-8b-Instruct-2024-10-09
5.42
5.95
4.89
160/160
RoLlama3.1-8b-Instruct-2025-04-23
6.43
6.78
6.09
160/160
RoLlama3.1-8b-Instruct-DPO-2024-10-09
6.21
6.74
5.69
160/160
RoLlama3.1-8b-Instruct-DPO-2025-04-23
7.00
7.30
6.70
160/160
+ + +## RoCulturaBench + + + + + + + + + + + + + + + + + + + + + + + + +
Model
Average
Answers in Ro
Llama-3.1-8B-Instruct
3.54
100/100
RoLlama3.1-8b-Instruct-2024-10-09
3.55
100/100
RoLlama3.1-8b-Instruct-2025-04-23
4.28
100/100
RoLlama3.1-8b-Instruct-DPO-2024-10-09
4.42
100/100
RoLlama3.1-8b-Instruct-DPO-2025-04-23
4.73
100/100
+ + + +## RoLlama3.1 Model Family + +| Model | Link | +|--------------------|:--------:| +|RoLlama3.1-8b-Instruct-2024-10-09| [link](https://huggingface.co/OpenLLM-Ro/RoLlama3.1-8b-Instruct-2024-10-09) | +|RoLlama3.1-8b-Instruct-2025-04-23| [link](https://huggingface.co/OpenLLM-Ro/RoLlama3.1-8b-Instruct-2025-04-23) | +|RoLlama3.1-8b-Instruct-DPO-2024-10-09| [link](https://huggingface.co/OpenLLM-Ro/RoLlama3.1-8b-Instruct-DPO-2024-10-09) | +|*RoLlama3.1-8b-Instruct-DPO-2025-04-23*| [link](https://huggingface.co/OpenLLM-Ro/RoLlama3.1-8b-Instruct-DPO-2025-04-23) | + + +## 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..2c5be64 --- /dev/null +++ b/config.json @@ -0,0 +1,40 @@ +{ + "_name_or_path": 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"normalized": false, + "rstrip": false, + "single_word": false, + "special": true + } + }, + "additional_special_tokens": [ + "<|eot_id|>", + "<|eom_id|>" + ], + "bos_token": "<|begin_of_text|>", + "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n {%- for arg_name, arg_val in tool_call.arguments | items %}\n {{- arg_name + '=\"' + arg_val + '\"' }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- else %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {%- endif %}\n {%- if builtin_tools is defined %}\n {#- This means we're in ipython mode #}\n {{- \"<|eom_id|>\" }}\n {%- else %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n", + "clean_up_tokenization_spaces": true, + "eos_token": "<|eot_id|>", + "model_input_names": [ + "input_ids", + "attention_mask" + ], + "model_max_length": 1000000000000000019884624838656, + "pad_token": "<|eot_id|>", + "padding_side": "right", + "split_special_tokens": false, + "tokenizer_class": "PreTrainedTokenizerFast" +}