prithivMLmods/Llama-Sentient-3.2-3B-Instruct

Llama-Sentient-3.2-3B-Instruct Modelfile

The Llama-Sentient-3.2-3B-Instruct model is a fine-tuned version of the Llama-3.2-3B-Instruct model, optimized for text generation tasks, particularly where instruction-following abilities are critical. This model is trained on the mlabonne/lmsys-arena-human-preference-55k-sharegpt dataset, which enhances its performance in conversational and advisory contexts, making it suitable for a wide range of applications.

File Name	Size	Description	Upload Status
.gitattributes	1.57 kB	Git attributes configuration file	Uploaded
README.md	42 Bytes	Initial commit README	Uploaded
config.json	1.04 kB	Configuration file	Uploaded
generation_config.json	248 Bytes	Generation configuration file	Uploaded
pytorch_model-00001-of-00002.bin	4.97 GB	PyTorch model file (part 1)	Uploaded (LFS)
pytorch_model-00002-of-00002.bin	1.46 GB	PyTorch model file (part 2)	Uploaded (LFS)
pytorch_model.bin.index.json	21.2 kB	Model index file	Uploaded
special_tokens_map.json	477 Bytes	Special tokens mapping	Uploaded
tokenizer.json	17.2 MB	Tokenizer JSON file	Uploaded (LFS)
tokenizer_config.json	57.4 kB	Tokenizer configuration file	Uploaded

Model Type	Size	Context Length	Link
GGUF	3B	-	🤗 Llama-Sentient-3.2-3B-Instruct-GGUF

Key Use Cases:

1. Conversational AI: Engage in intelligent dialogue, offering coherent responses and following instructions, useful for customer support and virtual assistants.
2. Text Generation: Generate high-quality, contextually appropriate content such as articles, summaries, explanations, and other forms of written communication based on user prompts.
3. Instruction Following: Follow specific instructions with accuracy, making it ideal for tasks that require structured guidance, such as technical troubleshooting or educational assistance.

The model uses a PyTorch-based architecture and includes a range of necessary files such as configuration files, tokenizer files, and model weight files for deployment.

Intended Applications:

• Chatbots for virtual assistance, customer support, or as personal digital assistants.
• Content Creation Tools, aiding in the generation of written materials, blog posts, or automated responses based on user inputs.
• Educational and Training Systems, providing explanations and guided learning experiences in various domains.
• Human-AI Interaction platforms, where the model can follow user instructions to provide personalized assistance or perform specific tasks.

With its strong foundation in instruction-following and conversational contexts, the Llama-Sentient-3.2-3B-Instruct model offers versatile applications for both general and specialized domains.