Rustamshry
/

Philosophy-chat

@@ -1,7 +1,7 @@
 ---
 base_model: unsloth/Qwen2.5-1.5B-Instruct
 library_name: peft
-pipeline_tag: text-generation
 tags:
 - base_model:adapter:unsloth/Qwen2.5-1.5B-Instruct
 - lora
@@ -9,202 +9,93 @@ tags:
 - transformers
 - trl
 - unsloth
 ---
 # Model Card for Model ID
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 ## Model Details
 ### Model Description
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 ### Framework versions
 - PEFT 0.17.0

 ---
 base_model: unsloth/Qwen2.5-1.5B-Instruct
 library_name: peft
+pipeline_tag: question-answering
 tags:
 - base_model:adapter:unsloth/Qwen2.5-1.5B-Instruct
 - lora
 - transformers
 - trl
 - unsloth
+license: mit
+datasets:
+- Heigke/stanford-enigma-philosophy-chat
+language:
+- en
 ---
 # Model Card for Model ID
+Stanford-philosophy is a fine-tuned version of Qwen2.5-1.5B-Instruct, trained specifically on philosophical texts. The model specializes in understanding and generating responses related to complex philosophical concepts, arguments, and debates.
 ## Model Details
 ### Model Description
+- **Language:** English
+- **License:** MIT
+- **Finetuned from model:** unsloth/Qwen2.5-1.5B-Instruct
+- **Fine-Tuning Method**: Supervised Fine-tuning with LoRA
+- **Domain**: Philosophy
+- **Dataset**: Heigke/stanford-enigma-philosophy-chat
 ## Uses
 ### Direct Use
+- Generating clear and concise explanations of philosophical concepts.
+- Providing structured responses to philosophical questions.
+- Assisting students, researchers, and enthusiasts in exploring philosophical arguments.
 ## Bias, Risks, and Limitations
+- While fine-tuned on philosophy, the model may still occasionally generate hallucinations or less precise interpretations of highly nuanced philosophical arguments.
+- The model does not replace expert human philosophical judgment.
 ## How to Get Started with the Model
+```
+from huggingface_hub import login
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
+login(token="")
+tokenizer = AutoTokenizer.from_pretrained("unsloth/Qwen2.5-1.5B-Instruct",)
+base_model = AutoModelForCausalLM.from_pretrained(
+    "unsloth/Qwen2.5-1.5B-Instruct",
+    device_map={"": 0}, token=""
+)
+model = PeftModel.from_pretrained(base_model,"Rustamshry/Stanford-philosophy")
+question = "According to William Whewell, what is necessary for gaining knowledge?"
+system = """
+You are an expert in philosophy.
+"""
+messages = [
+    {"role" : "system", "content" : system},
+    {"role" : "user",   "content" : question}
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize = False,
+)
+from transformers import TextStreamer
+_ = model.generate(
+    **tokenizer(text, return_tensors = "pt").to("cuda"),
+    max_new_tokens = 1024,
+    streamer = TextStreamer(tokenizer, skip_prompt = True),
+)
+```
+## Training Details
+### Training Data
+Roughly 27k questions and answers inspired by articles from Stanford Encyclopedia of Philosophy.
+The questions range all the way from Zombies to the concept of Abduction, from Metaphysics to Neuroethics and thus cover some of the essence of mathematics, logic and philosophy.
 ### Framework versions
 - PEFT 0.17.0