Trendyol-LLM-7b-base-v0.1
Maintainer: Trendyol
50
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The Trendyol-LLM-7b-base-v0.1 is a generative language model developed by Trendyol. It is based on the LLaMa2 7B model and has been fine-tuned using the LoRA method. The model comes in two variations - a base version and a chat version (Trendyol-LLM-7b-chat-v0.1).
While the base version has been fine-tuned on 10 billion tokens, the chat version has been fine-tuned on 180K instruction sets to optimize it for dialogue use cases. Similarly, the Turkcell-LLM-7b-v1 model is another Turkish-focused LLM that has been trained on 5 billion tokens of cleaned Turkish data and fine-tuned using the DORA and LORA methods.
Model inputs and outputs
Inputs
- The
Trendyol-LLM-7b-base-v0.1model takes text as input.
Outputs
- The model generates text as output.
Capabilities
The Trendyol-LLM-7b-base-v0.1 model is a capable language model that can be used for a variety of text generation tasks, such as summarization, question answering, and content creation. Its fine-tuning on 10 billion tokens allows it to generate high-quality, coherent text across a wide range of domains.
What can I use it for?
The Trendyol-LLM-7b-base-v0.1 model could be useful for projects that require Turkish language generation, such as chatbots, content creation tools, or question-answering systems. The chat version of the model (Trendyol-LLM-7b-chat-v0.1) may be particularly well-suited for building conversational AI assistants.
Things to try
One interesting aspect of the Trendyol-LLM-7b-base-v0.1 model is its use of the LoRA fine-tuning method, which has been shown to improve the efficiency and performance of language models. Developers could explore using LoRA for fine-tuning other language models on specific tasks or domains to see if it provides similar benefits.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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