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Mistral-portuguese-luana-7b-f16-gguf

Transformers
GGUF
Portuguese
Misral
Portuguese
7b
f16
Inference Endpoints
conversational
Model card Files Community
Mistral-portuguese-luana-7b-f16-gguf
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---
language:
- pt
license: apache-2.0
library_name: transformers
tags:
- Misral
- Portuguese
- 7b
- f16
- gguf
base_model: mistralai/Mistral-7B-Instruct-v0.2
datasets:
- pablo-moreira/gpt4all-j-prompt-generations-pt
- rhaymison/superset
---

# Mistral portuguese luana 7b f16 GGUF

<p align="center">
  <img src="https://raw.githubusercontent.com/rhaymisonbetini/huggphotos/main/luana7b.webp" width="50%" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
</p>

This GGUF model, derived from the Mixtrla Luana 7b, has been quantized in f16/half. The model was trained with a superset of 200,000 instructions in Portuguese, aiming to help fill the gap in models available in Portuguese. Tuned from the Mistral 7b, this model has been primarily adjusted for instructional tasks.

Remember that verbs are important in your prompt. Tell your model how to act or behave so that you can guide them along the path of their response. 
Important points like these help models (even smaller models like 7b) to perform much better.

```python
!git lfs install
!pip install langchain
!pip install langchain-community langchain-core
!pip install llama-cpp-python

!git clone https://huggingface.co/rhaymison/Mistral-portuguese-luana-7b-f16-gguf

def llamacpp():
    from langchain.llms import LlamaCpp
    from langchain.prompts import PromptTemplate
    from langchain.chains import LLMChain
    
    llm = LlamaCpp(
        model_path="/content/Mistral-portuguese-luana-7b-f16-gguf.gguf",
        n_gpu_layers=40,
        n_batch=512,
        verbose=True,
    )
    
    template = """<s>[INST] Abaixo está uma instrução que descreve uma tarefa, juntamente com uma entrada que fornece mais contexto.
    Escreva uma resposta que complete adequadamente o pedido.
    ### {question}
    [/INST]"""

    prompt = PromptTemplate(template=template, input_variables=["question"])
    
    llm_chain = LLMChain(prompt=prompt, llm=llm)
    
    question = "instrução: aja como um professor de matemática e me explique porque 2 + 2 = 4?"
    response = llm_chain.run({"question": question})
    print(response)

```
Output:
```text
Como professor de matemática, posso explicar que 2 + 2 = 4 é uma regra fundamental na matemática. 
Essa equação segue as propriedades da adição e de equivalência, como o princípio da idempotência (que diz que um elemento ou operador não altera nada se repetir), entre outras regras.
Assim, a equação 2 + 2 = 4 segue as propriedades fundamentais da adição na matemática, e é uma regra básica que toda criança deve aprender.  
```

### Comments

Any idea, help or report will always be welcome.

email: [email protected]

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