Update README.md

README.md

@@ -1,5 +1,45 @@
----
-license: apache-2.0
+---
+license: apache-2.0
+base_model:
+- mistralai/Mistral-7B-Instruct-v0.3
+datasets:
+- samzheng/SymbolicCode-CoT
+language:
+- en
+pipeline_tag: question-answering
+---
+model_name: "Mistral-7B-Math (Merged FP16 Checkpoint)" \
+repo: "samzheng/mistral-7b-math-merged"\
 base_model:
-- mistralai/Mistral-7B-Instruct-v0.3
----
+  name: "unsloth/mistral-7b-instruct-v0.3-bnb-4bit"
+  url: "https://huggingface.co/unsloth/mistral-7b-instruct-v0.3-bnb-4bit"\
+task: "Grade-school symbolic math word problems → Python code answers"\
+fine_tuning:
+  method: "LoRA adapters (r=16, α=16, dropout=0) merged into the base weights, FP16 precision"
+  parameters:
+    r: 16
+    alpha: 16
+    dropout: 0\
+dataset:
+  description: "6.7k Alpaca-formatted Q/A pairs with chain-of-thought + code"
+  splits:
+    - "symboliccode_cot_train"
+    - "symboliccode_cot_validation"\
+  language: python \
+  code: 
+  
+    from transformers import AutoModelForCausalLM, AutoTokenizer
+    model = AutoModelForCausalLM.from_pretrained(
+        "samzheng/mistral-7b-math-merged",
+        torch_dtype="auto", device_map="auto"
+    )
+    tok = AutoTokenizer.from_pretrained("samzheng/mistral-7b-math-merged")
+
+    prompt = """Below is an instruction that describes a task...
+    ### Instruction: Solve the problem using step-by-step reasoning and provide Python code.
+
+    ### Input: Solve for x: 2x + 5 = 17
+
+    ### Response:
+    """
+    print(tok.decode(model.generate(**tok(prompt, return_tensors="pt").to(model.device),max_new_tokens=256)[0], skip_special_tokens=True))