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Update README.md (#5)

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- Update README.md (9095279e307d3809907ead36bafbe8dce7f75918)

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@@ -1,5 +1,5 @@
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  ---
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- library_name: peft
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  base_model: codellama/CodeLlama-7b-Instruct-hf
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  license: apache-2.0
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  datasets:
@@ -42,6 +42,64 @@ Input : Text
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  Output : Text (Code)
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  **Params**
 
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  ---
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+ library_name: transformers
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  base_model: codellama/CodeLlama-7b-Instruct-hf
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  license: apache-2.0
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  datasets:
 
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  Output : Text (Code)
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+
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+ **Usage**
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+
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+ Using Transformers
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+ ```python
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+ #Import required libraries
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+ import torch
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+ from transformers import (
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+ AutoModelForCausalLM,
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+ AutoTokenizer
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+ )
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+
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+ #Load Model
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+ model_name = "semantixai/LloroV2"
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+ base_model = AutoModelForCausalLM.from_pretrained(
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+ model_name,
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+ return_dict=True,
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+ torch_dtype=torch.float16,
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+ device_map="auto",
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+ )
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+
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+ #Load Tokenizer
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+ tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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+
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+
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+ #Define Prompt
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+ user_prompt = "Desenvolva um algoritmo em Python para calcular a média e a mediana dos preços de vendas por tipo de material do produto."
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+ system = "Provide answers in Python without explanations, only the code"
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+ prompt_template = f"[INST] <<SYS>>\\n{system}\\n<</SYS>>\\n\\n{user_prompt}[/INST]"
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+
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+ #Call the model
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+ input_ids = tokenizer([prompt_template], return_tensors="pt")["input_ids"].to("cuda")
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+
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+
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+ outputs = base_model.generate(
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+ input_ids,
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+ do_sample=True,
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+ top_p=0.95,
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+ max_new_tokens=1024,
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+ temperature=0.1,
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+ )
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+
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+ #Decode and retrieve Output
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+ output_text = tokenizer.batch_decode(outputs, skip_prompt=True, skip_special_tokens=False)
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+ display(output_text)
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+ ```
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+
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+ Using an OpenAI compatible inference server (like [vLLM](https://docs.vllm.ai/en/latest/index.html))
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+ ```python
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+ from openai import OpenAI
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+
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+ client = OpenAI(
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+ api_key="EMPTY",
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+ base_url="http://localhost:8000/v1",
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+ )
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+ user_prompt = "Desenvolva um algoritmo em Python para calcular a média e a mediana dos preços de vendas por tipo de material do produto."
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+ completion = client.chat.completions.create(temperature=0.1,frequency_penalty=0.1,model="semantixai/LloroV2",messages=[{"role":"system","content":"Provide answers in Python without explanations, only the code"},{"role":"user","content":user_prompt}])
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+ ```
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  **Params**