Update README.md

README.md

@@ -1,41 +1,11 @@
 ---
 library_name: transformers
-tags: ['-medical']
+tags:
+- '-medical'
+datasets:
+- Mohammed-Altaf/medical-instruction-120k
 ---
 
-## Quickstart
-
-```python
-import torch
-from transformers import GPT2LMHeadModel, GPT2Tokenizer
-
-
-path = "Vidyuth/GPT2-finetuned-medical-instructions"
-device = "cuda" if torch.cuda.is_available() else "cpu"
-tokenizer = GPT2Tokenizer.from_pretrained(path)
-model = GPT2LMHeadModel.from_pretrained(path).to(device)
-
-prompt_input = (
-    "The conversation between human and AI assistant.\n"
-    "[|Human|] {input}\n"
-    "[|AI|]"
-)
-sentence = prompt_input.format_map({'input': "what is parkinson's disease?"})
-inputs = tokenizer(sentence, return_tensors="pt").to(device)
-
-with torch.no_grad():
-    beam_output = model.generate(**inputs,
-                                min_new_tokens=1, 
-                                max_length=512,
-                                num_beams=3,
-                                repetition_penalty=1.2,
-                                early_stopping=True,
-                                eos_token_id=198 
-                                )
-    print(tokenizer.decode(beam_output[0], skip_special_tokens=True))
-```
-
-
 ## Model Details
 
 ### Model Description
@@ -56,7 +26,7 @@ This is the model card of a 🤗 transformers model that has been pushed on the
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
+- **Repository:** [https://huggingface.co/jianghc/medical_chatbot]
 - **Paper [optional]:** [More Information Needed]
 - **Demo [optional]:** [More Information Needed]
 
@@ -97,7 +67,37 @@ Users (both direct and downstream) should be made aware of the risks, biases and
 ## How to Get Started with the Model
 
 
-[More Information Needed]
+
+```python
+import torch
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+
+path = "Vidyuth/GPT2-finetuned-medical-instructions"
+device = "cuda" if torch.cuda.is_available() else "cpu"
+tokenizer = GPT2Tokenizer.from_pretrained(path)
+model = GPT2LMHeadModel.from_pretrained(path).to(device)
+
+prompt_input = (
+    "The conversation between human and AI assistant.\n"
+    "[|Human|] {input}\n"
+    "[|AI|]"
+)
+sentence = prompt_input.format_map({'input': "what is parkinson's disease?"})
+inputs = tokenizer(sentence, return_tensors="pt").to(device)
+
+with torch.no_grad():
+    beam_output = model.generate(**inputs,
+                                min_new_tokens=1, 
+                                max_length=512,
+                                num_beams=3,
+                                repetition_penalty=1.2,
+                                early_stopping=True,
+                                eos_token_id=198 
+                                )
+    print(tokenizer.decode(beam_output[0], skip_special_tokens=True))
+```
+
 
 ## Training Details
 
@@ -222,6 +222,4 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 
 ## Model Card Contact
 
-[More Information Needed]
-
-
+[More Information Needed]