---
language:
- pt
license: apache-2.0
library_name: transformers
tags:
- portugues
- portuguese
- QA
- instruct
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
- rhaymison/superset
pipeline_tag: text-generation
---
# Llama 3 portuguese Tom cat 8b instruct GGUF
This model was trained with a superset of 300,000 chat in Portuguese.
The model comes to help fill the gap in models in Portuguese. Tuned from the Tom cat 8b instruct , the model was adjusted mainly for chat.
```python
!git lfs install
!pip install langchain
!pip install langchain-community langchain-core
!pip install llama-cpp-python
!git clone https://huggingface.co./rhaymison/Llama-3-portuguese-Tom-cat-8b-instruct-q8-gguf/
def llamacpp():
from langchain.llms import LlamaCpp
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
llm = LlamaCpp(
model_path="/content/Llama-3-portuguese-Tom-cat-8b-instruct-q8-gguf",
n_gpu_layers=40,
n_batch=512,
verbose=True,
)
template = f"""<|begin_of_text|><|start_header_id|>system<|end_header_id|>
Abaixo está uma instrução que descreve uma tarefa, juntamente com uma entrada que fornece mais contexto. Escreva uma resposta que complete adequadamente o pedido.<|eot_id|><|start_header_id|>user<|end_header_id|>
{ question }<|eot_id|><|start_header_id|>assistant<|end_header_id|>"""
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)
```
### Comments
Any idea, help or report will always be welcome.
email: rhaymisoncristian@gmail.com
