rhaymison
/

Mistral-portuguese-luana-7b-Mathematics

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 ---
 library_name: transformers
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 ---
 library_name: transformers
+license: apache-2.0
+datasets:
+- rhaymison/orca-math-portuguese-64k
+language:
+- pt
+pipeline_tag: text-generation
+base_model: rhaymison/Mistral-portuguese-luana-7b
+tags:
+- portuguese
+- math
+- mathematics
+- matematica
 ---
+# Mistral-portuguese-luana-7b-Mathematics
+<p align="center">
+  <img src="https://raw.githubusercontent.com/rhaymisonbetini/huggphotos/main/luana-math.webp" alt="Bode Logo" width="50%" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
+</p>
+Luana Mathematics is a tuned model of the Luana-7b based on the Mistral 7b architecture.
+This template has been fine-tuned with 64k math problems and solutions derived from Microsoft's Orca-Math.
+# How to use
+You can use the model in its normal form up to 4-bit quantization. Below we will use both approaches.
+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
+!pip install -q -U transformers
+!pip install -q -U accelerate
+!pip install -q -U bitsandbytes
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+model = AutoModelForCausalLM.from_pretrained("rhaymison/Mistral-portuguese-luana-7b-Mathematics", device_map= {"": 0})
+tokenizer = AutoTokenizer.from_pretrained("rhaymison/Mistral-portuguese-luana-7b-Mathematics")
+model.eval()
+```
+You can use with Pipeline but in this example i will use such as Streaming
+```python
+inputs = tokenizer([f"""<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.
+### instrução: Se eu emprestei 100 reais para o meu irmão para que ele me pague em 3 vezes. O juros do empréstimo é 5% do valor do emprestimo por mes. Quanto meu irmão terá que me pagar no total?
+[/INST]"""], return_tensors="pt")
+inputs.to(model.device)
+streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+_ = model.generate(**inputs, streamer=streamer, max_new_tokens=200)
+```
+```python
+```
+# 4bits
+```python
+from transformers import BitsAndBytesConfig
+import torch
+nb_4bit_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_compute_dtype=torch.bfloat16,
+    bnb_4bit_use_double_quant=True
+)
+model = AutoModelForCausalLM.from_pretrained(
+    base_model,
+    quantization_config=bnb_config,
+    device_map={"": 0}
+)
+```
+### Comments
+Any idea, help or report will always be welcome.
+email: rhaymisoncristian@gmail.com
+ <div style="display:flex; flex-direction:row; justify-content:left">
+    <a href="https://www.linkedin.com/in/heleno-betini-2b3016175/" target="_blank">
+    <img src="https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white">
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+    <img src="https://img.shields.io/badge/GitHub-100000?style=for-the-badge&logo=github&logoColor=white">
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