Instructions to use scq21cs2dsadsa/MyAwesomeModel-TestRepository with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scq21cs2dsadsa/MyAwesomeModel-TestRepository with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="scq21cs2dsadsa/MyAwesomeModel-TestRepository")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("scq21cs2dsadsa/MyAwesomeModel-TestRepository") model = AutoModel.from_pretrained("scq21cs2dsadsa/MyAwesomeModel-TestRepository", device_map="auto") - Notebooks
- Google Colab
- Kaggle
scq21cs2dsadsa commited on
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681ea5e
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Parent(s): 0b134d4
Update benchmark scores to 3 decimal places in original README structure
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README.md
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<div align="center">
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| **Core Reasoning**
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| **Language Understanding** | Reading Comprehension | 0.815
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| **Generation**
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| **Specialized**
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</div>
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### Overall Performance Summary
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The MyAwesomeModel demonstrates strong performance across all
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## 3. Chat Website & API Platform
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We offer a chat interface and API for you to interact with MyAwesomeModel. Please check our official website for more details.
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search_answer_en_template = \
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'''# The following contents are the search results related to the user's message:
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{search_results}
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In the search results I provide to you, each result is formatted as [webpage X begin]...[webpage X end], where X represents the numerical index of each article. Please cite the context at the end of the relevant sentence when appropriate. Use the citation format [citation:X] in the corresponding part of your answer. If a sentence is derived from multiple contexts, list all relevant citation numbers, such as [citation:3][citation:5]. Be sure not to cluster all citations at the end; instead, include them in the corresponding parts of
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When responding, please keep the following points in mind:
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- Today is {cur_date}.
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- Not all content in the search results is closely related to the user's question. You need to evaluate and filter the search results based on the question.
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## 6. Contact
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If you have any questions, please raise an issue on our GitHub repository or contact us at contact@MyAwesomeModel.ai.
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<div align="center">
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| | Benchmark | Model1 | Model2 | Model1-v2 | MyAwesomeModel |
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| **Core Reasoning Tasks** | Math Reasoning | 0.510 | 0.535 | 0.521 | 0.875 |
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| | Logical Reasoning | 0.789 | 0.801 | 0.810 | 0.842 |
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| | Common Sense | 0.716 | 0.702 | 0.725 | 0.789 |
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| **Language Understanding** | Reading Comprehension | 0.671 | 0.685 | 0.690 | 0.815 |
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| | Question Answering | 0.582 | 0.599 | 0.601 | 0.763 |
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| | Text Classification | 0.803 | 0.811 | 0.820 | 0.851 |
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| | Sentiment Analysis | 0.777 | 0.781 | 0.790 | 0.822 |
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| **Generation Tasks** | Code Generation | 0.615 | 0.631 | 0.640 | 0.794 |
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| | Creative Writing | 0.588 | 0.579 | 0.601 | 0.736 |
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| | Dialogue Generation | 0.621 | 0.635 | 0.639 | 0.778 |
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| | Summarization | 0.745 | 0.755 | 0.760 | 0.803 |
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| **Specialized Capabilities**| Translation | 0.782 | 0.799 | 0.801 | 0.837 |
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| | Knowledge Retrieval | 0.651 | 0.668 | 0.670 | 0.751 |
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| | Instruction Following | 0.733 | 0.749 | 0.751 | 0.864 |
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| | Safety Evaluation | 0.718 | 0.701 | 0.725 | 0.889 |
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</div>
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### Overall Performance Summary
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The MyAwesomeModel demonstrates strong performance across all evaluated benchmark categories, with particularly notable results in reasoning and generation tasks.
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## 3. Chat Website & API Platform
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We offer a chat interface and API for you to interact with MyAwesomeModel. Please check our official website for more details.
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search_answer_en_template = \
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'''# The following contents are the search results related to the user's message:
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{search_results}
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In the search results I provide to you, each result is formatted as [webpage X begin]...[webpage X end], where X represents the numerical index of each article. Please cite the context at the end of the relevant sentence when appropriate. Use the citation format [citation:X] in the corresponding part of your answer. If a sentence is derived from multiple contexts, list all relevant citation numbers, such as [citation:3][citation:5]. Be sure not to cluster all citations at the end; instead, include them in the corresponding parts of the answer.
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When responding, please keep the following points in mind:
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- Today is {cur_date}.
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- Not all content in the search results is closely related to the user's question. You need to evaluate and filter the search results based on the question.
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## 6. Contact
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If you have any questions, please raise an issue on our GitHub repository or contact us at contact@MyAwesomeModel.ai.
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```
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