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--- |
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license: mit |
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datasets: |
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- squad_v2 |
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- quac |
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language: |
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- en |
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widget: |
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- text: >- |
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when: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes |
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ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an |
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Argentine professional footballer who plays as a forward for and captains |
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both Major League Soccer club Inter Miami and the Argentina national team. |
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Widely regarded as one of the greatest players of all time, Messi has won a |
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record seven Ballon d'Or awards[note 2] and a record six European Golden |
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Shoes, and in 2020 he was named to the Ballon d'Or Dream Team. Until leaving |
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the club in 2021, he had spent his entire professional career with |
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Barcelona, where he won a club-record 34 |
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- text: >- |
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where: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes |
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ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an |
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Argentine professional footballer who plays as a forward for and captains |
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both Major League Soccer club Inter Miami and the Argentina national team. |
|
Widely regarded as one of the greatest players of all time, Messi has won a |
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record seven Ballon d'Or awards[note 2] and a record six European Golden |
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Shoes, and in 2020 he was named to the Ballon d'Or Dream Team. Until leaving |
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the club in 2021, he had spent his entire professional career with |
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Barcelona, where he won a club-record 34 |
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- text: >- |
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how: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes |
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ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an |
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Argentine professional footballer who plays as a forward for and captains |
|
both Major League Soccer club Inter Miami and the Argentina national team. |
|
Widely regarded as one of the greatest players of all time, Messi has won a |
|
record seven Ballon d'Or awards[note 2] and a record six European Golden |
|
Shoes, and in 2020 he was named to the Ballon d'Or Dream Team. Until leaving |
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the club in 2021, he had spent his entire professional career with |
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Barcelona, where he won a club-record 34 |
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- text: >- |
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what: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes |
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ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an |
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Argentine professional footballer who plays as a forward for and captains |
|
both Major League Soccer club Inter Miami and the Argentina national team. |
|
Widely regarded as one of the greatest players of all time, Messi has won a |
|
record seven Ballon d'Or awards[note 2] and a record six European Golden |
|
Shoes, and in 2020 he was named to the Ballon d'Or Dream Team. Until leaving |
|
the club in 2021, he had spent his entire professional career with |
|
Barcelona, where he won a club-record 34 |
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- text: >- |
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where: Egypt (Egyptian Arabic: مصر Maṣr Egyptian Arabic pronunciation: |
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[mɑsˤr]), officially the Arab Republic of Egypt, is a transcontinental |
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country spanning the northeast corner of Africa and the Sinai Peninsula in |
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the southwest corner of Asia. It is bordered by the Mediterranean Sea to the |
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north, the Gaza Strip of Palestine and Israel to the northeast, the Red Sea |
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to the east, Sudan to the south, and Libya to the west. The Gulf of Aqaba in |
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the northeast separates Egypt from Jordan and Saudi Arabia. Cairo is the |
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capital and largest city of Egypt, while Alexandria, the second-largest |
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city, is an important industrial and tourist hub at the Mediterranean |
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coast.[11] At approximately 100 million inhabitants, Egypt is the 14th-most |
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populated country in the world, and the third-most populated in Africa, |
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behind Nigeria and Ethiopia. |
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- text: >- |
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where: There is evidence of rock carvings along the Nile terraces and in |
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desert oases. In the 10th millennium BCE, a culture of hunter-gatherers and |
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fishers was replaced by a grain-grinding culture. Climate changes or |
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overgrazing around 8000 BCE began to desiccate the pastoral lands of Egypt, |
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forming the Sahara. Early tribal peoples migrated to the Nile River where |
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they developed a settled agricultural economy and more centralized society. |
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- text: >- |
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when: By about 6000 BCE, a Neolithic culture took root in the Nile |
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Valley.[31] During the Neolithic era, several predynastic cultures developed |
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independently in Upper and Lower Egypt. The Badarian culture and the |
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successor Naqada series are generally regarded as precursors to dynastic |
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Egypt. The earliest known Lower Egyptian site, Merimda, predates the |
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Badarian by about seven hundred years. Contemporaneous Lower Egyptian |
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communities coexisted with their southern counterparts for more than two |
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thousand years. The earliest known evidence of Egyptian hieroglyphic |
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inscriptions appeared during the predynastic period on Naqada III pottery |
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vessels, dated to about 3200 BCE.[32] |
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- text: >- |
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whose : or the next three millennia. Egyptian culture flourished during this |
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long period and remained distinctively Egyptian in its religion, arts, |
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language and customs. The first two ruling dynasties of a unified Egypt set |
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the stage for the Old Kingdom period, c. 2700–2200 BCE, which constructed |
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many pyramids, most notably the Third Dynasty pyramid of Djoser and the |
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Fourth Dynasty Giza pyramids. |
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- text: >- |
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who:The First Intermediate Period ushered in a time of political upheaval |
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for about 150 years.[33] Stronger Nile floods and stabilisation of |
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government, however, brought back renewed prosperity for the country in the |
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Middle Kingdom c. 2040 BCE, reaching a peak during the reign of Pharaoh |
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Amenemhat III. A second period of disunity heralded the arrival of the first |
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foreign ruling dynasty in Egypt, that of the Semitic Hyksos. The Hyksos |
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invaders took over much of Lower Egypt around 1650 BCE and founded a new |
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capital at Avaris. They were driven out by an Upper Egyptian force led by |
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Ahmose I, who founded the Eighteenth Dynasty and relocated the capital from |
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Memphis to Thebes. |
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library_name: transformers |
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tags: |
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- generate answers |
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- question generator |
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- generate text |
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- nlp |
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- dataset maker |
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- flan t5 |
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- t5 |
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- extract quetions from context |
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- extract quetion |
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--- |
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# Model Card for QA_GeneraToR |
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Excited 😄 to share with you my very first model 🤖 for generating question-answering datasets! This incredible model takes articles 📜 or web pages, and all you need to provide is a prompt and context. It works like magic ✨, generating both the question and the answer. The prompt can be anything – "what," "who," "where" ... etc ! 😅 |
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I've harnessed the power of the flan-t5 model 🚀, which has truly elevated the quality of the results. You can find all the code and details in the repository right here: https://lnkd.in/dhE5s_qg |
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And guess what? I've even deployed the project, so you can experience the magic firsthand: https://lnkd.in/diq-d3bt ❤️ |
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Join me on this exciting journey into #nlp, #textgeneration, #t5, #deeplearning, and #huggingface. Your feedback and collaboration are more than welcome! 🌟 |
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# my fine tuned model |
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>This model is fine tuned to generate a question with answers from a context , why that can be very usful this can help you to generate a dataset from a book article any thing you would to make from it dataset and train another model on this dataset , give the model any context with pre prometed of quation you want + context and it will extarct question + answer for you |
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this are promted i use |
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>[ "which", "how", "when", "where", "who", "whom", "whose", "why", |
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"which", "who", "whom", "whose", "whereas", |
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"can", "could", "may", "might", "will", "would", "shall", "should", |
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"do", "does", "did", "is", "are", "am", "was", "were", "be", "being", "been", |
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"have", "has", "had", "if", "is", "are", "am", "was", "were", "do", "does", "did", "can", "could", |
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"will", "would", "shall", "should", "might", "may", "must", |
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"may", "might", "must"] |
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> |
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# orignal model info |
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<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/flan2_architecture.jpg" |
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alt="drawing" width="600"/> |
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# Code |
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```python |
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from transformers import AutoTokenizer, AutoModelForQuestionAnswering |
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model_name="mohamedemam/Question_generator" |
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def generate_question_answer(context, prompt, model_name="mohamedemam/Question_generator"): |
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""" |
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Generates a question-answer pair using the provided context, prompt, and model. |
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Args: |
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context: String containing the text or URL of the source material. |
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prompt: String starting with a question word (e.g., "what," "who"). |
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model_name: Optional string specifying the model name (default: google/flan-t5-base). |
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Returns: |
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A tuple containing the generated question and answer strings. |
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""" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForQuestionAnswering.from_pretrained(model_name) |
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inputs = tokenizer(context, return_tensors="pt") |
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with torch.no_grad(): |
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outputs = model(**inputs) |
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start_scores, end_scores = outputs.start_logits, outputs.end_logits |
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answer_start = torch.argmax(start_scores) |
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answer_end = torch.argmax(end_scores) + 1 # Account for inclusive end index |
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answer = tokenizer.convert_tokens_to_strings(tokenizer.convert_ids_to_tokens(inputs["input_ids"][answer_start:answer_end]))[0] |
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question = f"{prompt} {answer}" # Formulate the question using answer |
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return question, answer |
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# Example usage |
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context = "The capital of France is Paris." |
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prompt = "What" |
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question, answer = generate_question_answer(context, prompt) |
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print(f"Question: {question}") |
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print(f"Answer: {answer}") |
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``` |
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