Update README.md

README.md

@@ -12,6 +12,7 @@ tags:
 - nlp
 - dataset maker
 ---
+
 # Model Card for FLAN-T5 large
 
 <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/flan2_architecture.jpg"
@@ -44,8 +45,8 @@ As mentioned in the first few lines of the abstract :
 
 
 - **Model type:** Language model
-- **Language(s) (NLP):** English, Spanish, Japanese, Persian, Hindi, French, Chinese, Bengali, Gujarati, German, Telugu, Italian, Arabic, Polish, Tamil, Marathi, Malayalam, Oriya, Panjabi, Portuguese, Urdu, Galician, Hebrew, Korean, Catalan, Thai, Dutch, Indonesian, Vietnamese, Bulgarian, Filipino, Central Khmer, Lao, Turkish, Russian, Croatian, Swedish, Yoruba, Kurdish, Burmese, Malay, Czech, Finnish, Somali, Tagalog, Swahili, Sinhala, Kannada, Zhuang, Igbo, Xhosa, Romanian, Haitian, Estonian, Slovak, Lithuanian, Greek, Nepali, Assamese, Norwegian
-- **License:** Apache 2.0
+- **Language(s) (NLP):** English
+- **License:** mit 
 - **Related Models:** [All FLAN-T5 Checkpoints](https://huggingface.co/models?search=flan-t5)
 - **Original Checkpoints:** [All Original FLAN-T5 Checkpoints](https://github.com/google-research/t5x/blob/main/docs/models.md#flan-t5-checkpoints)
 - **Resources for more information:**
@@ -68,10 +69,10 @@ Find below some example scripts on how to use the model in `transformers`:
 
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 
-tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large")
+tokenizer = T5Tokenizer.from_pretrained("mohamedemam/QA_GeneraToR")
+model = T5ForConditionalGeneration.from_pretrained("mohamedemam/QA_GeneraToR")
 
-input_text = "translate English to German: How old are you?"
+input_text = r"when: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an 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"
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids
 
 outputs = model.generate(input_ids)
@@ -89,10 +90,10 @@ print(tokenizer.decode(outputs[0]))
 # pip install accelerate
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 
-tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large", device_map="auto")
+tokenizer = T5Tokenizer.from_pretrained("mohamedemam/QA_GeneraToR")
+model = T5ForConditionalGeneration.from_pretrained("mohamedemam/QA_GeneraToR", device_map="auto")
 
-input_text = "translate English to German: How old are you?"
+input_text = r"when: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an 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"
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
 
 outputs = model.generate(input_ids)
@@ -113,10 +114,10 @@ print(tokenizer.decode(outputs[0]))
 import torch
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 
-tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large", device_map="auto", torch_dtype=torch.float16)
+tokenizer = T5Tokenizer.from_pretrained("mohamedemam/QA_GeneraToR")
+model = T5ForConditionalGeneration.from_pretrained("mohamedemam/QA_GeneraToR", device_map="auto", torch_dtype=torch.float16)
 
-input_text = "translate English to German: How old are you?"
+input_text = r"when: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an 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"
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
 
 outputs = model.generate(input_ids)
@@ -134,10 +135,10 @@ print(tokenizer.decode(outputs[0]))
 # pip install bitsandbytes accelerate
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 
-tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large", device_map="auto", load_in_8bit=True)
+tokenizer = T5Tokenizer.from_pretrained("mohamedemam/QA_GeneraToR")
+model = T5ForConditionalGeneration.from_pretrained("mohamedemam/QA_GeneraToR", device_map="auto", load_in_8bit=True)
 
-input_text = "translate English to German: How old are you?"
+input_text = r"when: Lionel Andrés Messi[note 1] (Spanish pronunciation: [ljoˈnel anˈdɾes ˈmesi] (listen); born 24 June 1987), also known as Leo Messi, is an 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"
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
 
 outputs = model.generate(input_ids)