Update README.md

README.md

@@ -78,22 +78,25 @@ probs = torch.softmax(logits[:, -1, :], dim=-1)
 next_token = torch.multinomial(probs, num_samples=1)
 generated_ids = torch.cat([input_ids, next_token], dim=1)
 generated_text = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
+clean_text = generated_text.replace('Ġ','')
 print(generated_text)
 ```
 
 ### Alternative: Using the `generate()` Method
 
 ```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import AutoTokenizer, AutoModel, AutoModelForCausalLM
 
 tokenizer = AutoTokenizer.from_pretrained("codewithdark/latent-recurrent-depth-lm")
-model = AutoModelForCausalLM.from_pretrained("codewithdark/latent-recurrent-depth-lm")
+model = AutoModel.from_pretrained("codewithdark/latent-recurrent-depth-lm", trust_remote_code=True)
 
 prompt = "In the realm of language modeling"
 input_ids = tokenizer(prompt, return_tensors="pt").input_ids
-generated_ids = model.generate(input_ids, max_length=50, num_iterations=3, temperature=0.8, top_k=50)
+generated_ids = model.generate(input_ids, max_length=50, num_iterations=10, temperature=0.5, top_k=50)
 generated_text = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
-print(generated_text)
+clean_text = generated_text.replace('Ġ','')
+print(clean_text)
+
 ```
 
 ## Ethical Considerations