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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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  ## Model Details
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-
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- ### Model Description
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-
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- <!-- Provide a longer summary of what this model is. -->
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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-
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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-
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- ### Model Sources [optional]
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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-
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- ## Uses
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-
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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-
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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-
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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- Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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- ## Training Details
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- ### Training Data
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- <!-- 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. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- [More Information Needed]
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- 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).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ### Compute Infrastructure
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- #### Hardware
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- #### Software
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- **APA:**
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  ---
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+ language:
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+ - en
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+ - fr
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+ - es
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+ - pt
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+ tags:
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+ - falcon3
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  ---
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+ # Falcon3-7B-Base
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+ **Falcon3** family of Open Foundation Models is a set of pretrained and instruct LLMs ranging from 1B to 10B.
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+ This repository contains the **Falcon3-3B-Base**. It achieves strong results on reasoning, language understanding, instruction following, code and mathematics tasks.
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+ Falcon3-3B-Base supports 4 languages (english, french, spanish, portuguese) and a context length up to 8K.
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+ Falcon3-3B-Base pruned (depth + width) from Falcon3-7B-Base, was effeciently trained on only 100 GT using a knowledge distillation objective.
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+ ⚠️ **This is a raw, pretrained model, which should be further finetuned for most usecases.**
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  ## Model Details
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+ - Architecture
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+ - Transformer based causal decoder only architecture
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+ - 22 decoder blocks
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+ - Grouped query attention (GQA) for faster inference: 12 query heads and 4 KV heads
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+ - Wider head dimension: 256
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+ - High RoPE value to support long context understanding: 1000042
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+ - 8k context length
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+ - 131k vocab size
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+ - Pruned and Healed from Falcon3-7B-Base on only 100 Gigatokens of datasets comprising of web, code, STEM, high quality and mutlilingual data using 2048 H100 GPU chips
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+ - Supports EN, FR, ES, PT
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+ - Developed by [Technology Innovation Institute](https://www.tii.ae)
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+ - License: TII Falcon-LLM License 2.0
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+ - Model Release Date: December 2024
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+
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+
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+ ## Getting started
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+
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+ <details>
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+ <summary> Click to expand </summary>
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+
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+ ```python
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+ import torch
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+ from transformers import pipeline
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+
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+ pipe = pipeline(
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+ "text-generation",
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+ model="tiiuae/Falcon3-3B-Base",
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+ torch_dtype=torch.bfloat16,
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+ device_map="auto"
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+ )
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+ response = pipe("Question: How many hours in one day? Answer: ")
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+ print(response[0]['generated_text'])
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+ ```
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+
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+ </details>
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+
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+ <br>
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+
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+ # Benchmarks
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+ We report in the following table our internal pipeline benchmarks:
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+
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+
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+
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+ <table border="1" style="width: 100%; text-align: center; border-collapse: collapse;">
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+ <colgroup>
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+ <col style="width: 10%;">
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+ <col style="width: 10%;">
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+ <col style="width: 7%;">
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+ <col style="width: 7%;">
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+ <col style="width: 7%;">
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+ <col style="width: 7%;">
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+ <col style="background-color: rgba(80, 15, 213, 0.5); width: 7%;">
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+ </colgroup>
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+ <thead>
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+ <tr>
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+ <th>Category</th>
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+ <th>Benchmark</th>
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+ <th>Llama3.2-3B</th>
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+ <th>Qwen2.5-3B</th>
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+ <th>Minitron-4B</th>
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+ <th>Falcon3-3B-Base</th>
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+ </tr>
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+ </thead>
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+ <tbody>
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+ <tr>
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+ <td rowspan="3">General</td>
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+ <td>MMLU (5-shot)</td>
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+ <td>56.1</td>
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+ <td>65.6</td>
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+ <td>58.6</td>
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+ <td>55.5</td>
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+ </tr>
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+ <tr>
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+ <td>MMLU-PRO (5-shot)</td>
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+ <td>24.9</td>
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+ <td>31.99</td>
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+ <td>26.21</td>
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+ <td>28.77</td>
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+ </tr>
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+ <tr>
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+ <td>IFEval</td>
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+ <td>12.83</td>
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+ <td>27</td>
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+ <td>22.81</td>
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+ <td>27.67</td>
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+
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+ </tr>
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+ <tr>
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+ <td rowspan="2">Math</td>
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+ <td>GSM8K (5-shot)</td>
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+ <td>26.68</td>
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+ <td>68.99</td>
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+ <td>25.7</td>
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+ <td>63.91</td>
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+ </tr>
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+ <tr>
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+ <td>MATH(4-shot)</td>
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+ <td>1.39</td>
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+ <td>8.43</td>
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+ <td>1.73</td>
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+ <td>9.38</td>
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+ </tr>
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+ <tr>
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+ <td rowspan="4">Reasoning</td>
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+ <td>Arc Challenge (25-shot)</td>
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+ <td>50.76</td>
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+ <td>55.54</td>
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+ <td>50.34</td>
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+ <td>54.86</td>
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+ </tr>
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+ <tr>
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+ <td>GPQA (0-shot)</td>
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+ <td>27.49</td>
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+ <td>27.53</td>
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+ <td>38.6</td>
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+ <td>31.15</td>
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+ </tr>
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+ <tr>
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+ <td>MUSR (0-shot)</td>
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+ <td>35.24</td>
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+ <td>43.03</td>
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+ <td>42.13</td>
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+ <td>37.5</td>
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+ </tr>
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+ <tr>
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+ <td>BBH (3-shot)</td>
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+ <td>38.59</td>
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+ <td>46.12</td>
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+ <td>40.85</td>
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+ <td>44.23</td>
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+ </tr>
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+ <tr>
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+ <td rowspan="4">CommonSense Understanding</td>
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+ <td>PIQA (0-shot)</td>
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+ <td>77.42</td>
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+ <td>78.89</td>
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+ <td>78.29</td>
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+ <td>75.62</td>
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+ </tr>
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+ <tr>
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+ <td>SciQ (0-shot)</td>
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+ <td>92.7</td>
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+ <td>95.6</td>
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+ <td>96.1</td>
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+ <td>93.1</td>
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+ </tr>
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+ <tr>
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+ <td>Winogrande (0-shot)</td>
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+ <td>69.69</td>
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+ <td>68.82</td>
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+ <td>68.35</td>
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+ <td>64.64</td>
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+ </tr>
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+ <tr>
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+ <td>OpenbookQA (0-shot)</td>
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+ <td>43.2</td>
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+ <td>42.2</td>
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+ <td>43</td>
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+ <td>39.4</td>
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+ </tr>
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+ </tbody>
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+ </table>
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+
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+
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+ # Citation
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+ If Falcon3 family were helpful to your work, feel free to give us a cite.
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+
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+ ```
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+ @misc{Falcon3,
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+ title = {The Falcon 3 family of Open Models},
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+ author = {TII Team},
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+ month = {December},
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+ year = {2024}
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+ }
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+ ```