File size: 8,425 Bytes
d9cd092 f8594f5 d9cd092 f8594f5 d9cd092 f8594f5 d9cd092 f8594f5 d9cd092 f8594f5 d9cd092 f8594f5 d9cd092 f8594f5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 |
---
license: apache-2.0
datasets:
- nicholasKluge/instruct-aira-dataset-v2
language:
- pt
metrics:
- accuracy
library_name: transformers
pipeline_tag: text-generation
tags:
- alignment
- instruction tuned
- text generation
- conversation
- assistant
widget:
- text: "<s><instruction>Cite algumas bandas de rock famosas da década de 1960.</instruction>"
example_title: Exemplo
- text: "<s><instruction>Quantos planetas existem no sistema solar?</instruction>"
example_title: Exemplo
- text: "<s><instruction>Qual é o futuro do ser humano?</instruction>"
example_title: Exemplo
- text: "<s><instruction>Qual o sentido da vida?</instruction>"
example_title: Exemplo
- text: "<s><instruction>Como imprimir hello world em python?</instruction>"
example_title: Exemplo
- text: "<s><instruction>Invente uma história sobre um encanador com poderes mágicos.</instruction>"
example_title: Exemplo
inference:
parameters:
repetition_penalty: 1.2
temperature: 0.2
top_k: 30
top_p: 0.3
max_new_tokens: 200
length_penalty: 0.3
early_stopping: true
co2_eq_emissions:
emissions: 2.53
source: CodeCarbon
training_type: fine-tuning
geographical_location: United States of America
hardware_used: NVIDIA A100-SXM4-40GB
---
# TeenyTinyLlama-460m-Chat
TeenyTinyLlama is a pair of small foundational models trained in Brazilian Portuguese.
This repository contains a version of [TeenyTinyLlama-460m](https://huggingface.co/nicholasKluge/TeenyTinyLlama-460m) (`TeenyTinyLlama-460m-Chat`) fine-tuned on the [Instruct-Aira Dataset version 2.0](https://huggingface.co/datasets/nicholasKluge/instruct-aira-dataset-v2).
## Details
- **Number of Epochs:** 3
- **Batch size:** 4
- **Optimizer:** `torch.optim.AdamW` (warmup_steps = 1e3, learning_rate = 1e-5, epsilon = 1e-8)
- **GPU:** 1 NVIDIA A100-SXM4-40GB
- **Carbon emissions** stats are logged in this [file](emissions.csv).
This repository has the [source code](https://github.com/Nkluge-correa/Aira) used to train this model.
## Usage
The following special tokens are used to mark the user side of the interaction and the model's response:
`<instruction>`What is a language model?`</instruction>`A language model is a probability distribution over a vocabulary.`</s>`
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
tokenizer = AutoTokenizer.from_pretrained('nicholasKluge/TeenyTinyLlama-460m-Chat')
model = AutoModelForCausalLM.from_pretrained('nicholasKluge/TeenyTinyLlama-460m-Chat')
model.eval()
model.to(device)
question = input("Entre seu prompt aqui: ")
inputs = tokenizer("<instruction>" + question + "</instruction>", return_tensors="pt").to(device)
responses = model.generate(**inputs, num_return_sequences=2)
print(f"Pergunta: 👤 {question}\n")
for i, response in enumerate(responses):
print(f'Resposta {i+1}: 🤖 {tokenizer.decode(response, skip_special_tokens=True).replace(question, "")}')
```
The model will output something like:
```markdown
>>>Question: 👤 Qual a capital do Brasil?
>>>Response 1: 🤖 A capital do Brasil é Brasília.
>>>Response 2: 🤖 A capital do Brasil é Brasília.
```
## Limitations
- **Hallucinations:** This model can produce content that can be mistaken for truth but is, in fact, misleading or entirely false, i.e., hallucination.
- **Biases and Toxicity:** This model inherits the social and historical stereotypes from the data used to train it. Given these biases, the model can produce toxic content, i.e., harmful, offensive, or detrimental to individuals, groups, or communities.
- **Unreliable Code:** The model may produce incorrect code snippets and statements. These code generations should not be treated as suggestions or accurate solutions.
- **Language Limitations:** The model is primarily designed to understand standard Portuguese (BR). Other languages might challenge its comprehension, leading to potential misinterpretations or errors in response.
- **Repetition and Verbosity:** The model may get stuck on repetition loops (especially if the repetition penalty during generations is set to a meager value) or produce verbose responses unrelated to the prompt it was given.
## Benchmarks
| Models | Average | [ARC](https://arxiv.org/abs/1803.05457) | [Hellaswag](https://arxiv.org/abs/1905.07830) | [MMLU](https://arxiv.org/abs/2009.03300) | [TruthfulQA](https://arxiv.org/abs/2109.07958) |
|-------------------------------------------------------------------------------------|---------|-----------------------------------------|-----------------------------------------------|------------------------------------------|------------------------------------------------|
| [TeenyTinyLlama-460m](https://huggingface.co/nicholasKluge/TeenyTinyLlama-460m) | 33.01 | 29.40 | 33.00 | 28.55 | 41.10 |
| [Bloom-560m](https://huggingface.co/bigscience/bloom-560m) | 32.13 | 24.74* | 37.15* | 24.22* | 42.44* |
| [Xglm-564M](https://huggingface.co/facebook/xglm-564M) | 31.97 | 25.56 | 34.64* | 25.18* | 42.53 |
| [TeenyTinyLlama-160m](https://huggingface.co/nicholasKluge/TeenyTinyLlama-160m) | 31.16 | 26.15 | 29.29 | 28.11 | 41.12 |
| [Pythia-160m](https://huggingface.co/EleutherAI/pythia-160m-deduped) | 31.16 | 24.06* | 31.39* | 24.86* | 44.34* |
| [OPT-125m](https://huggingface.co/facebook/opt-125m) | 30.80 | 22.87 | 31.47 | 26.02 | 42.87 |
| [Gpt2-portuguese-small](https://huggingface.co/pierreguillou/gpt2-small-portuguese) | 30.22 | 22.48* | 29.62* | 27.36* | 41.44* |
| [Gpt2-small](https://huggingface.co/gpt2) | 29.97 | 21.48* | 31.60* | 25.79* | 40.65* |
| [Multilingual GPT](https://huggingface.co/ai-forever/mGPT) | 29.45 | 24.79 | 26.37* | 25.17* | 41.50 |
* Evaluations on benchmarks were performed using the [Language Model Evaluation Harness](https://github.com/EleutherAI/lm-evaluation-harness) (by [EleutherAI](https://www.eleuther.ai/)). Thanks to [Laiviet](https://github.com/laiviet/lm-evaluation-harness) for translating some of the tasks in the LM-Evaluation-Harness.
## Cite as 🤗
```latex
@misc{nicholas22llama,
doi = {10.5281/zenodo.6989727},
url = {https://huggingface.co/nicholasKluge/TeenyTinyLlama-460m},
author = {Nicholas Kluge Corrêa},
title = {TeenyTinyLlama},
year = {2023},
publisher = {HuggingFace},
journal = {HuggingFace repository},
}
```
## Funding
This repository was built as part of the RAIES ([Rede de Inteligência Artificial Ética e Segura](https://www.raies.org/)) initiative, a project supported by FAPERGS - ([Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul](https://fapergs.rs.gov.br/inicial)), Brazil.
## License
TeenyTinyLlama-460m-Chat is licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more details. |