Update README.md

README.md

@@ -9,6 +9,8 @@ datasets:
 language:
 - zh
 pipeline_tag: text-generation
+base_model:
+- microsoft/Phi-3-mini-4k-instruct
 ---
 
 
@@ -36,8 +38,8 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 model_id = "Mike0307/Phi-3-mini-4k-instruct-chinese-lora"
 model = AutoModelForCausalLM.from_pretrained(
     model_id, 
-    device_map="mps", # Change mps if not MacOS
-    torch_dtype=torch.float32,  # try float16 for M1 chip
+    device_map="mps", # mps is for MacOS users
+    torch_dtype=torch.float32,  # try float16 if needed
     trust_remote_code=True,
     attn_implementation="eager", # without flash_attn
 )
@@ -53,7 +55,7 @@ input_text = "<|user|>將這五種動物分成兩組。\n老虎、鯊魚、大
 inputs = tokenizer(
     input_text, 
     return_tensors="pt"
-).to(torch.device("mps")) # Change mps if not MacOS
+).to(torch.device("mps")) # mps is for MacOS users
 
 outputs = model.generate(
     **inputs, 
@@ -100,5 +102,4 @@ generated_text = tokenizer.decode(
 
 [This reference](https://huggingface.co/Mike0307/text2vec-base-chinese-rag#example-of-langchain-rag) shows how to customize langchain llm with this phi-3 lora model.
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6414866f1cbd604c9217c7d0/RrBoHJINfrSWtCNkePs7g.png)
-
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6414866f1cbd604c9217c7d0/RrBoHJINfrSWtCNkePs7g.png)