Create README.md

README.md

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+---
+language:
+- pt
+license: apache-2.0
+library_name: transformers
+tags:
+- portugues
+- portuguese
+- QA
+- instruct
+- phi
+- gguf
+- f16
+base_model: microsoft/Phi-3-mini-4k-instruct
+datasets:
+- rhaymison/superset
+pipeline_tag: text-generation
+---
+
+# Phi3 portuguese tom cat 4k instruct GGUF
+
+<p align="center">
+  <img src="https://raw.githubusercontent.com/rhaymisonbetini/huggphotos/main/tom-cat.webp"  width="50%" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
+</p>
+
+This GGUF model, derived from the Phi3 Tom cat 4k, has been quantized in f16. The model was trained with a superset of 300,000 instructions in Portuguese, aiming to help fill the gap in models available in Portuguese. 
+Tuned from Phi3-4k, this model has been primarily adjusted for instructional tasks.
+
+This model was trained with a superset of 300,000 instructions in Portuguese. 
+The model comes to help fill the gap in models in Portuguese. Tuned from the   microsoft/Phi-3-mini-4k.
+
+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 4b) 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/phi-3-portuguese-tom-cat-4k-instruct-f16-gguf
+
+def llamacpp():
+    from langchain.llms import LlamaCpp
+    from langchain.prompts import PromptTemplate
+    from langchain.chains import LLMChain
+    
+    llm = LlamaCpp(
+        model_path="/content/phi-3-portuguese-tom-cat-4k-instruct-f16-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)
+
+```
+
+
+
+### 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/rhaymison-cristian-betini-2b3016175/" target="_blank">
+    <img src="https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white">
+  </a>
+  <a href="https://github.com/rhaymisonbetini" target="_blank">
+    <img src="https://img.shields.io/badge/GitHub-100000?style=for-the-badge&logo=github&logoColor=white">
+  </a>