Name override with rsLoRA(rank=128, alpha=256)

README.md

@@ -2,6 +2,7 @@
 base_model: SicariusSicariiStuff/Impish_LLAMA_3B
 datasets:
 - KingNish/reasoning-base-20k
+- piotr25691/thea-name-overrides
 language:
 - en
 license: llama3.2
@@ -17,9 +18,9 @@ tags:
 
 # Model Description
 
-A work in progress uncensored roleplay reasoning Llama 3.2 3B model trained on reasoning data.
+An uncensored roleplay reasoning Llama 3.2 3B model trained on reasoning data.
 
-Since I used different training code, it is unknown whether it generates the same kind of reasoning.
+It has been trained using improved training code, and gives an improved performance.
 Here is what inference code you should use:
 ```py
 from transformers import AutoModelForCausalLM, AutoTokenizer
@@ -27,7 +28,7 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 MAX_REASONING_TOKENS = 1024
 MAX_RESPONSE_TOKENS = 512
 
-model_name = "piotr25691/thea-3b-25r"
+model_name = "piotr25691/thea-rp-3b-25r"
 
 model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
 tokenizer = AutoTokenizer.from_pretrained(model_name)
@@ -43,7 +44,7 @@ reasoning_inputs = tokenizer(reasoning_template, return_tensors="pt").to(model.d
 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)
+print("REASONING: " + reasoning_output)
 
 # Generate answer
 messages.append({"role": "reasoning", "content": reasoning_output})

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tokenizer.json

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