Update README.md

README.md

@@ -3,8 +3,12 @@ tags:
 - autotrain
 - text-generation
 widget:
-- text: "I love AutoTrain because "
-license: other
+- text: 'I love AutoTrain because '
+license: apache-2.0
+datasets:
+- manjunathshiva/autotrain-data-GRADE3B-7B-02
+language:
+- en
 ---
 
 # Model Trained Using AutoTrain
@@ -16,25 +20,43 @@ This model was trained using AutoTrain. For more information, please visit [Auto
 ```python
 
 from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model_path = "PATH_TO_THIS_REPO"
-
-tokenizer = AutoTokenizer.from_pretrained(model_path)
-model = AutoModelForCausalLM.from_pretrained(
-    model_path,
-    device_map="auto",
-    torch_dtype='auto'
+from peft import PeftModel
+import torch
+access_token = "<HF_TOKEN>"
+
+
+tokenizer = AutoTokenizer.from_pretrained(
+        "meta-llama/Llama-2-7b-chat-hf"
+    )
+
+
+base_model =  AutoModelForCausalLM.from_pretrained(
+    'meta-llama/Llama-2-7b-chat-hf',
+    token=access_token,
+    trust_remote_code=True,
+    #device_map="auto",    #Uncomment if you hava a good GPU Memory
+    torch_dtype=torch.float16,
+    offload_folder="offload/"
+)
+model = PeftModel.from_pretrained(
+    base_model,
+    'manjunathshiva/GRADE3B-7B-02-0',
+    token=access_token,
+    offload_folder="offload/"
+    
 ).eval()
 
-# Prompt content: "hi"
+# Prompt content: "When is Maths Unit Test 2?"
 messages = [
-    {"role": "user", "content": "hi"}
+    {"role": "user", "content": "When is Maths Unit Test 2?"}
 ]
 
 input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt')
-output_ids = model.generate(input_ids.to('cuda'))
+#output_ids = model.generate(input_ids.to('cuda'))  #Uncomment if you have CUDA and comment below line
+output_ids = model.generate(input_ids=input_ids, temperature=0.01 )
 response = tokenizer.decode(output_ids[0][input_ids.shape[1]:], skip_special_tokens=True)
 
-# Model response: "Hello! How can I assist you today?"
+# Model response: "<Outputs Date>"
 print(response)
+
 ```