Update README.md

README.md

@@ -12,6 +12,100 @@ tags:
 - sft
 ---
 
+1 - # alpaca_prompt = Copied from above
+FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+inputs = tokenizer(
+[
+    alpaca_prompt.format(
+#        "Continue the fibonnaci sequence.", # instruction
+#        "1, 1, 2, 3, 5, 8", # input
+        "", # output - leave this blank for generation!
+    )
+], return_tensors = "pt").to("cuda")
+
+outputs = model.generate(**inputs, max_new_tokens = 128, use_cache = True)
+tokenizer.batch_decode(outputs)
+
+['Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Input:\nContinue the fibonnaci sequence.\n\n### Output:\n1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765, 10946, 17711, 28657, 46368, 75025, 121393, 196728, 318101']
+
+2 - # alpaca_prompt = Copied from above
+FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+inputs = tokenizer(
+[
+    alpaca_prompt.format(
+#        "What is fibonacci sequence?", # instruction
+        "", # input
+        "", # output - leave this blank for generation!
+    )
+], return_tensors = "pt").to("cuda")
+
+from transformers import TextStreamer
+text_streamer = TextStreamer(tokenizer)
+_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 256)
+
+Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Input:
+What is fibonacci sequence?
+
+### Output:
+The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding ones, usually starting with 0 and 1. The sequence goes like this: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765, 10946, 17711, 28657, 46368, 75025, 121393, 196728, 328101, 544829, 973530, 1518361, 2492891, 4011452, 6504307, 9518768, 15023075
+
+3 - if False:
+    from unsloth import FastLanguageModel
+    model, tokenizer = FastLanguageModel.from_pretrained(
+        model_name = "lora_model", # YOUR MODEL YOU USED FOR TRAINING
+        max_seq_length = max_seq_length,
+        dtype = dtype,
+        load_in_4bit = load_in_4bit,
+    )
+    FastLanguageModel.for_inference(model) # Enable native 2x faster inference
+
+# alpaca_prompt = You MUST copy from above!
+
+inputs = tokenizer(
+[
+    alpaca_prompt.format(
+#        "Crie uma IA. Ela será treinada para conversar por chat e escrever códigos em python conforme solicitada, após ser treinada para essas tarefas.", # instruction
+        "", # input
+        "", # output - leave this blank for generation!
+    )
+], return_tensors = "pt").to("cuda")
+
+from transformers import TextStreamer
+text_streamer = TextStreamer(tokenizer)
+_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 4096)
+
+Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Input:
+Crie uma IA. Ela será treinada para conversar por chat e escrever codigos em python conforme solicitada, após ser treinada para essas tarefas.
+
+### Output:
+Here is a simple Python program that uses the OpenAI's ChatGPT API to simulate a chatbot:
+
+```python
+import openai
+from openai import ChatGPT
+
+# Initialize the ChatGPT API
+openai.api_key = "YOUR_API_KEY"
+
+# Create a ChatGPT model
+model = ChatGPT(model_name="gpt-3.5-turbo")
+
+# Create a prompt
+prompt = "Write a python program that takes a number as input and prints out the square of that number."
+
+# Send the prompt to the ChatGPT model
+response = model.create(input=prompt)
+
+# Print the response
+print(response)
+```
+
+This program will output a Python program that takes a number as input and prints out the square of that number.<|endoftext|>
+
 # Uploaded  model
 
 - **Developed by:** Ramikan-BR