Update README.md

README.md

@@ -1,200 +1,126 @@
 ---
-library_name: transformers
+language:
+- en
 tags:
 - falcon3
 ---
 
-# Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+#  Table of Contents
 
+0. [TL;DR](#TL;DR)
+1. [Model Details](#model-details)
+2. [Usage](#usage)
+3. [Training Details](#training-details)
+4. [Evaluation](#evaluation)
 
 
-## Model Details
+# TL;DR
 
-### Model Description
+# Model Details
 
-<!-- Provide a longer summary of what this model is. -->
+## Model Description
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+- **Developed by:** [https://www.tii.ae](https://www.tii.ae)
+- **Model type:** Causal decoder-only
+- **Architecture:** Transformer-base
+- **Language(s) (NLP):** Mainly English
+- **License:** TII Falcon-Mamba License 2.0
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+<br>
 
-### Model Sources [optional]
+# Usage
 
-<!-- Provide the basic links for the model. -->
+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):
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+## Using the Pytorch model with 🤗 transformers
 
-## Uses
+### Running the model on a CPU
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+<details>
+<summary> Click to expand </summary>
 
-### Direct Use
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+tokenizer = AutoTokenizer.from_pretrained("tiiuae/Falcon3-7B-Base")
+model = AutoModelForCausalLM.from_pretrained("tiiuae/Falcon3-7B-Base")
 
-[More Information Needed]
+input_text = "Question: How many hours in one day? Answer: "
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids
 
-### Downstream Use [optional]
+outputs = model.generate(input_ids)
+print(tokenizer.decode(outputs[0]))
+```
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+</details>
 
-[More Information Needed]
+### Running the model on a GPU
 
-### Out-of-Scope Use
+<details>
+<summary> Click to expand </summary>
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+```python
+# pip install accelerate
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-[More Information Needed]
+tokenizer = AutoTokenizer.from_pretrained("tiiuae/Falcon3-7B-Base")
+model = AutoModelForCausalLM.from_pretrained("tiiuae/Falcon3-7B-Base", device_map="auto")
 
-## Bias, Risks, and Limitations
+input_text = "Question: How many hours in one day? Answer: "
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+outputs = model.generate(input_ids)
+print(tokenizer.decode(outputs[0]))
+```
 
-[More Information Needed]
+</details>
 
-### Recommendations
+### Running the model on a GPU using `torch.compile`
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+<details>
+<summary> Click to expand </summary>
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-## How to Get Started with the Model
+tokenizer = AutoTokenizer.from_pretrained("tiiuae/Falcon3-7B-Base")
+model = AutoModelForCausalLM.from_pretrained("tiiuae/Falcon3-7B-Base", torch_dtype=torch.bfloat16).to(0)
 
-Use the code below to get started with the model.
+model = torch.compile(model)
 
-[More Information Needed]
+input_text = "Question: How many hours in one day? Answer: "
+input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to("cuda")
 
-## Training Details
+outputs = model.generate(input_ids)
+print(tokenizer.decode(outputs[0]))
+```
 
-### Training Data
+</details>
 
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
 
-[More Information Needed]
+# Training Details
 
-### Training Procedure
+## Training Data
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+## Training Procedure
 
-#### Preprocessing [optional]
+### Training Hyperparameters
 
-[More Information Needed]
+| **Hyperparameter** | **Value**  | **Comment**                               |
+|--------------------|------------|-------------------------------------------|
+| Precision          | `bfloat16` |                                           |
+| Optimizer          | AdamW      |                                           |
+| Max learning rate  |      | Following a WSD (warmup-stable-decay) learning rate schedule |
+| Weight decay       |        |                                           |
+| Batch size         |        |                                           |
 
 
-#### Training Hyperparameters
+# Evaluation
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
 
-#### Speeds, Sizes, Times [optional]
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+# Citation
 
-[More Information Needed]
 
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]