README.md

---
library_name: transformers
model-index:
- name: internlm-chatbode-20b
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: ENEM Challenge (No Images)
      type: eduagarcia/enem_challenge
      split: train
      args:
        num_few_shot: 3
    metrics:
    - type: acc
      value: 65.78
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BLUEX (No Images)
      type: eduagarcia-temp/BLUEX_without_images
      split: train
      args:
        num_few_shot: 3
    metrics:
    - type: acc
      value: 58.69
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: OAB Exams
      type: eduagarcia/oab_exams
      split: train
      args:
        num_few_shot: 3
    metrics:
    - type: acc
      value: 43.33
      name: accuracy
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Assin2 RTE
      type: assin2
      split: test
      args:
        num_few_shot: 15
    metrics:
    - type: f1_macro
      value: 91.53
      name: f1-macro
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: Assin2 STS
      type: eduagarcia/portuguese_benchmark
      split: test
      args:
        num_few_shot: 15
    metrics:
    - type: pearson
      value: 78.95
      name: pearson
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: FaQuAD NLI
      type: ruanchaves/faquad-nli
      split: test
      args:
        num_few_shot: 15
    metrics:
    - type: f1_macro
      value: 81.36
      name: f1-macro
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: HateBR Binary
      type: ruanchaves/hatebr
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: f1_macro
      value: 81.72
      name: f1-macro
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: PT Hate Speech Binary
      type: hate_speech_portuguese
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: f1_macro
      value: 73.66
      name: f1-macro
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: tweetSentBR
      type: eduagarcia/tweetsentbr_fewshot
      split: test
      args:
        num_few_shot: 25
    metrics:
    - type: f1_macro
      value: 70.11
      name: f1-macro
    source:
      url: >-
        https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard?query=recogna-nlp/internlm-chatbode-20b
      name: Open Portuguese LLM Leaderboard
language:
- pt
pipeline_tag: text-generation
---

# internlm-chatbode-20b

<!--- PROJECT LOGO -->
<p align="center">
  <img src="https://huggingface.co/recogna-nlp/internlm-chatbode-7b/resolve/main/_1add1e52-f428-4c7c-bab2-3c6958e029fa.jpeg" alt="ChatBode Logo" width="400" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
</p>

O InternLm-ChatBode é um modelo de linguagem ajustado para o idioma português, desenvolvido a partir do modelo [InternLM2](https://huggingface.co/internlm/internlm2-chat-20b). Este modelo foi refinado através do processo de fine-tuning utilizando o dataset UltraAlpaca.

## Características Principais

- **Modelo Base:** [internlm/internlm2-chat-20b](internlm/internlm2-chat-20b)
- **Dataset para Fine-tuning:** UltraAlpaca
- **Treinamento:** O treinamento foi realizado a partir do fine-tuning, usando QLoRA, do internlm2-chat-20b.

## Exemplo de uso

A seguir um exemplo de código de como carregar e utilizar o modelo:

```python
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("recogna-nlp/internlm-chatbode-20b", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("recogna-nlp/internlm-chatbode-20b", torch_dtype=torch.float16, trust_remote_code=True).cuda()
model = model.eval()
response, history = model.chat(tokenizer, "Olá", history=[])
print(response)
response, history = model.chat(tokenizer, "O que é o Teorema de Pitágoras? Me dê um exemplo", history=history)
print(response)
```

As respostas podem ser geradas via stream utilizando o método `stream_chat`:

```python
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

model_path = "recogna-nlp/internlm-chatbode-20b"
model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.float16, trust_remote_code=True).cuda()
tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)

model = model.eval()
length = 0
for response, history in model.stream_chat(tokenizer, "Olá", history=[]):
    print(response[length:], flush=True, end="")
    length = len(response)
```


# Open Portuguese LLM Leaderboard Evaluation Results  

Detailed results can be found [here](https://huggingface.co/datasets/eduagarcia-temp/llm_pt_leaderboard_raw_results/tree/main/recogna-nlp/internlm-chatbode-20b) and on the [🚀 Open Portuguese LLM Leaderboard](https://huggingface.co/spaces/eduagarcia/open_pt_llm_leaderboard)

|          Metric          |  Value  |
|--------------------------|---------|
|Average                   |**71.68**|
|ENEM Challenge (No Images)|    65.78|
|BLUEX (No Images)         |    58.69|
|OAB Exams                 |    43.33|
|Assin2 RTE                |    91.53|
|Assin2 STS                |    78.95|
|FaQuAD NLI                |    81.36|
|HateBR Binary             |    81.72|
|PT Hate Speech Binary     |    73.66|
|tweetSentBR               |    70.11|