Guilherme34
/

Reasoning-2.6-fixed

@@ -1,199 +1,43 @@
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+This is a Remake, refined and better version of the KingNish Reasoning model.
+```pip install peft
+pip install -U bitsandbytes
+pip install -U transformers
+```
+```
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM
+MAX_REASONING_TOKENS = 1024
+MAX_RESPONSE_TOKENS = 512
+model = AutoModelForCausalLM.from_pretrained("Guilherme34/Reasoning-2.6", token="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")
+tokenizer = AutoTokenizer.from_pretrained("Guilherme34/Reasoning-2.6")
+prompt = "hey, how are you?"
+messages = [
+    {"role": "user", "content": prompt}
+]
+# Generate reasoning
+reasoning_template = tokenizer.apply_chat_template(messages, tokenize=False, add_reasoning_prompt=True)
+reasoning_inputs = tokenizer(reasoning_template, return_tensors="pt").to(model.device)
+reasoning_ids = model.generate(**reasoning_inputs, max_new_tokens=MAX_REASONING_TOKENS)
+reasoning_output = tokenizer.decode(reasoning_ids[0, reasoning_inputs.input_ids.shape[1]:], skip_special_tokens=True)
+# print("REASONING: " + reasoning_output)
+# Generate answer
+messages.append({"role": "reasoning", "content": reasoning_output})
+response_template = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+response_inputs = tokenizer(response_template, return_tensors="pt").to(model.device)
+response_ids = model.generate(**response_inputs, max_new_tokens=MAX_RESPONSE_TOKENS)
+response_output = tokenizer.decode(response_ids[0, response_inputs.input_ids.shape[1]:], skip_special_tokens=True)
+print("ANSWER: " + response_output)
+```