Update README.md

README.md

@@ -34,8 +34,32 @@ widget:
 
 The Tamil-Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an improved instruct fine-tuned version of [Tamil-Mistral-7B-Instruct-v0.1](https://huggingface.co/Hemanth-thunder/Tamil-Mistral-7B-Instruct-v0.1).
 Tamil LLM: A Breakthrough in Tamil Language Understanding In the realm of language models, the fine-tuned Tamil Mistral model represents a significant advancement. Unlike its English counterpart, the Tamil Mistral model is specifically tailored to comprehend and generate text in the Tamil language. This innovation addresses a critical gap, as the English Mistral model fails to effectively engage with Tamil, a language rich in culture and heritage. Through extensive fine-tuning with a base Tamil Mistral model, this iteration has been meticulously enhanced to grasp the nuances and intricacies of the Tamil language. As a result, we are delighted to present a revolutionary model that enables seamless interaction through text. Welcome to the future of conversational Tamil language processing with our instructive model.
+
  
+## Kaggle demo link
+https://www.kaggle.com/code/hemanthkumar21/tamil-mistral-instruct-v0-1-demo/
 
+```python
+from transformers import  (AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig,TextStreamer,pipeline)
+import torch
+model_name = "Hemanth-thunder/Tamil-Mistral-7B-Instruct-v0.1"
+nf4_config = BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_quant_type="nf4",bnb_4bit_use_double_quant=True,
+   bnb_4bit_compute_dtype=torch.bfloat16
+)
+model = AutoModelForCausalLM.from_pretrained(model_name,device_map='auto',quantization_config=nf4_config,use_cache=False,low_cpu_mem_usage=True )
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+tokenizer.pad_token = tokenizer.eos_token
+tokenizer.padding_side = "right"
+streamer = TextStreamer(tokenizer)
+pipe = pipeline("text-generation" ,model=model, tokenizer=tokenizer ,do_sample=True, repetition_penalty=1.15,top_p=0.95,streamer=streamer)
+prompt = create_prompt("வாழ்க்கையில் ஆரோக்கியமாக இருப்பது எப்படி?")
+result=pipe(prompt,max_length=512,pad_token_id=tokenizer.eos_token_id)
+
+```
+```
+result:
+- உடற்பயிற்சி - ஆரோக்கியமான உணவை உண்ணுங்கள் -2 புகைபிடிக்காதே - தவறாமல் உடற்பயிற்சி செய்</s>
+```
 ## Instruction format
 
 To harness the power of instruction fine-tuning, your prompt must be encapsulated within <s> and </s> tokens. This instructional format revolves around three key elements: Instruction, Input, and Response. The Tamil Mistral instruct model is adept at engaging in conversations based on this structured template.
@@ -64,33 +88,6 @@ prompt_template =<s>"""சரியான பதிலுடன் வேலை
 
 ```
 
-This format is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating) via the `apply_chat_template()` method:
-
-## Kaggle demo link
-https://www.kaggle.com/code/hemanthkumar21/tamil-mistral-instruct-v0-1-demo/
-
-```python
-from transformers import  (AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig,TextStreamer,pipeline)
-import torch
-model_name = "Hemanth-thunder/Tamil-Mistral-7B-Instruct-v0.1"
-nf4_config = BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_quant_type="nf4",bnb_4bit_use_double_quant=True,
-   bnb_4bit_compute_dtype=torch.bfloat16
-)
-model = AutoModelForCausalLM.from_pretrained(model_name,device_map='auto',quantization_config=nf4_config,use_cache=False,low_cpu_mem_usage=True )
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-tokenizer.pad_token = tokenizer.eos_token
-tokenizer.padding_side = "right"
-streamer = TextStreamer(tokenizer)
-pipe = pipeline("text-generation" ,model=model, tokenizer=tokenizer ,do_sample=True, repetition_penalty=1.15,top_p=0.95,streamer=streamer)
-prompt = create_prompt("வாழ்க்கையில் ஆரோக்கியமாக இருப்பது எப்படி?")
-result=pipe(prompt,max_length=512,pad_token_id=tokenizer.eos_token_id)
-
-```
-```
-result:
-- உடற்பயிற்சி - ஆரோக்கியமான உணவை உண்ணுங்கள் -2 புகைபிடிக்காதே - தவறாமல் உடற்பயிற்சி செய்</s>
-```
-
 ## Python function to format query
 ```python
 def create_prompt(query,prompt_template=prompt_template):
@@ -133,4 +130,11 @@ This should not be required after transformers-v4.33.4.
 
 The Mistral 7B Instruct model is a quick demonstration that the base model can be easily fine-tuned to achieve compelling performance. 
 It does not have any moderation mechanisms. We're looking forward to engaging with the community on ways to
-make the model finely respect guardrails, allowing for deployment in environments requiring moderated outputs.
+make the model finely respect guardrails, allowing for deployment in environments requiring moderated outputs.
+
+## How to Cite
+@misc{Tamil-Mistral-7B-Instruct-v0.1, 
+      url={[https://huggingface.co/Hemanth-thunder/Tamil-Mistral-7B-Instruct-v0.1]https://huggingface.co/Hemanth-thunder/Tamil-Mistral-7B-Instruct-v0.1)}, 
+      title={Tamil-Mistral-7B-Instruct-v0.1}, 
+      author={"hemanth kuamr"}
+}