Update README.md

README.md

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----
-license: apache-2.0
----
+---
+language: 
+- multilingual
+
+license: apache-2.0
+---
+
+# Model Card for FLAN-T5 large
+
+
+
+#  Table of Contents
+
+0. [TL;DR](#TL;DR)
+1. [Model Details](#model-details)
+2. [Usage](#usage)
+3. [Training Details](#training-details)
+4. [Evaluation](#evaluation)
+
+
+# TL;DR
+
+# Model Details
+
+## Model Description
+
+
+- **Model type:** Language model
+- **Language(s) (NLP):** English
+- **License:** Apache 2.0
+
+# Usage
+
+Find below some example scripts on how to use the model in `transformers` (Make sure to have the latest transformers, or the one built from source):
+
+## Using the Pytorch model
+
+### Running the model on a CPU
+
+<details>
+<summary> Click to expand </summary>
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("tiiuae/sindibad-7b")
+model = AutoModelForCausalLM.from_pretrained("tiiuae/sindibad-7b")
+
+input_text = "Question: How many hours in one day? Answer: "
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+
+outputs = model.generate(input_ids)
+print(tokenizer.decode(outputs[0]))
+```
+
+</details>
+
+### Running the model on a GPU
+
+<details>
+<summary> Click to expand </summary>
+
+```python
+# pip install accelerate
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("tiiuae/sindibad-7b")
+model = AutoModelForCausalLM.from_pretrained("tiiuae/sindibad-7b", device_map="auto")
+
+input_text = "Question: How many hours in one day? Answer: "
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
+
+outputs = model.generate(input_ids)
+print(tokenizer.decode(outputs[0]))
+```
+
+</details>
+
+### Running the model on a GPU using different precisions
+
+#### FP16
+
+<details>
+<summary> Click to expand </summary>
+
+```python
+# pip install accelerate
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("tiiuae/sindibad-7b")
+model = AutoModelForCausalLM.from_pretrained("tiiuae/sindibad-7b", device_map="auto", torch_dtype=torch.float16)
+
+input_text = "Question: How many hours in one day? Answer: "
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
+
+outputs = model.generate(input_ids)
+print(tokenizer.decode(outputs[0]))
+```
+
+</details>
+
+#### INT8
+
+<details>
+<summary> Click to expand </summary>
+
+```python
+# pip install bitsandbytes accelerate
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("tiiuae/sindibad-7b")
+model = AutoModelForCausalLM.from_pretrained("tiiuae/sindibad-7b", device_map="auto", load_in_8bit=True)
+
+input_text = "Question: How many hours in one day? Answer: "
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
+
+outputs = model.generate(input_ids)
+print(tokenizer.decode(outputs[0]))
+```
+
+</details>
+
+
+# Training Details
+
+## Training Data
+
+
+
+## Training Procedure
+
+
+# Evaluation
+
+## Testing Data, Factors & Metrics
+
+
+## Results 
+
+