| --- |
| library_name: peft |
| base_model: meta-math/MetaMath-Mistral-7B |
| license: apache-2.0 |
| pipeline_tag: text2text-generation |
| language: |
| - en |
| --- |
| |
| # Model Card for Model ID |
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| <!-- Provide a quick summary of what the model is/does. --> |
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| ## Model Details |
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| ### Model Description |
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| <!-- Provide a longer summary of what this model is. --> |
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| - **Developed by:** Timofej Kiselev (tfshaman) |
| - **Model type:** Mistral finetuned for solving MWPs using symbolic expressions with SymPy |
| - **Language(s) (NLP):** English, Python with SymPy |
| - **License:** Apache-2.0 |
| - **Finetuned from model [optional]:** meta-math/MetaMath-Mistral-7B |
| - **Trained on:** Research Center for Informatics | CTU Prague, RCI cluster |
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| ### Model Sources [optional] |
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| <!-- Provide the basic links for the model. --> |
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| - **Repository:** [More Information Needed] |
| - **Paper [optional]:** https://dspace.cvut.cz/bitstream/handle/10467/115466/F3-BP-2024-Kiselev-Timofej-Thesis_Timofej_Kiselev.pdf |
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| ## Uses |
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| <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
| Input format: |
| f"Question {your_math_word_problem}\n\nAnswer: " |
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| ### Direct Use |
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| <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
| ```python |
| bnb_config = BitsAndBytesConfig( |
| load_in_4bit=True, |
| bnb_4bit_use_double_quant=True, |
| bnb_4bit_quant_type="nf4", |
| bnb_4bit_compute_dtype=torch.bfloat16, |
| ) |
| config = PeftConfig.from_pretrained("tfshaman/SymPy-Mistral") |
| base_model = AutoModelForCausalLM.from_pretrained("meta-math/MetaMath-Mistral-7B", quantization_config=bnb_config) |
| tokenizer = AutoTokenizer.from_pretrained("tfshaman/SymPy-Mistral-tokenizer", use_fast=False, padding_side="left") |
| base_model.resize_token_embeddings(len(tokenizer)) |
| tokenizer.pad_token = "<s>" |
| tokenizer.padding_side='left' |
| model = PeftModel.from_pretrained(base_model, "tfshaman/SymPy-Mistral", quantization_config=bnb_config) |
| model = model.to("cuda") |
| |
| ``` |
| [More Information Needed] |
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| ### Downstream Use [optional] |
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| <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
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| [More Information Needed] |
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| ## Citation |
| <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
| @mastersthesis{timofej2024velke, |
| title={Velk{\'e} jazykov{\'e} modely pro numerick{\'e} dotazy}, |
| author={Timofej, Kiselev}, |
| type={{B.S.} thesis}, |
| year={2024}, |
| school={{\v{C}}esk{\'e} vysok{\'e} u{\v{c}}en{\'\i} technick{\'e} v Praze. Vypo{\v{c}}etn{\'\i} a informa{\v{c}}n{\'\i} centrum.} |
| } |
| |
| ### Framework versions |
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| - PEFT 0.7.1 |
