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---
license: other
language:
- en
pipeline_tag: conversational
inference: false
tags:
- AI
- ConversationalAI
---
<h1 style="text-align: center">LLmRa-1.3B-V2</h1>
<h2 style="text-align: center">A conversational Open Pre-trained Transformer Language Model fine-tune.</h2>
**LLmRa 1.3B-V2**, as a proof-of-concept fine-tune of [facebook/opt-1.3b](https://huggingface.co/facebook/opt-1.3b) optimized for dialogue.
**Disclaimer:** NSFW data was included in the fine-tuning of this model. Although SFW inputs will usually result in SFW outputs, you are advised to **chat at your own risk. This model is not suitable for use by minors.**
**Warning:** This model is **NOT** suitable for use by minors. **It will output X-rated content under certain circumstances.**
**Model Fine-Tuned on LLmRa-100K conversational dataset - small version**
---
## Usage Format
To effectively utilize the model, follow this structured format for engaging text-based conversations:
**1. Initialization**
Here is how you can define the personality of the language model:
```
<|system|>[Persona]
```
- **Persona**: You can define a specific persona or context for the AI, but it's optional. It can be a character, a role, or just a style of interaction.
**2. AI Introduction**
```
<|user|>[User input]<|model|>
```
- Users can start the conversation by entering their message within `<|user|>` and closing with `<|model|>`.
---
### Example Usage:
Here's an example of how to start a conversation with the AI:
```
<|system|>I'm here to provide information and assistance on a wide range of topics.
<|model|>Hello! Welcome to our AI-powered assistant. How can I assist you today?
<|user|>Tell me about the history of artificial intelligence.
<|model|>
```
Continue the conversation as needed. This structured format helps maintain a smooth and engaging interaction with the AI.
You are not required to include `User`, you can change it to your prefered name or leave it blank You may also add the AI name, example:
```
<|user|>YourNameHere: Hello.<|model|>CharacterName:
```
You can also use this instruct prompt example:
```
<|system|>What is one plus one?<|model|>
```
## Loading The Model
To use the model and interact with it, use the Python code below:
```Python
from transformers import (AutoModelForCausalLM,
AutoTokenizer,
pipeline,
)
model = AutoModelForCausalLM.from_pretrained('L-R/LLmRa-1.3B-V2')
tokenizer = AutoTokenizer.from_pretrained('L-R/LLmRa-1.3B-V2')
pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=100)
input_question = 'QUESTION HERE'
question_formatted = f'<|system|>{input_question}<|model|>'
result = pipe(question_formatted)
print(f"[model]: {result[0]['generated_text'][len(question_formatted):]}")
```
## Known issues
Model doesn't some of the times follow instructions. |