Kosmos E V A A v9 8 B

Introduction
Kosmos-EVAA-v9-8B is a language model created through the merging of pre-trained models using the SLERP method. It leverages technologies from the Hugging Face ecosystem, specifically utilizing the 'transformers' library.

Architecture
The Kosmos-EVAA-v9-8B model is a result of merging two distinct models: Kosmos-EVAA-v8-8B and Kosmos-EVAA-v3-8B. The merging process involved combining layers from each model (layers 0 to 32) using specific parameters and methods to optimize performance.

Training
Kosmos-EVAA-v9-8B was generated by merging Kosmos-EVAA-v8-8B and Kosmos-EVAA-v3-8B. The SLERP (Spherical Linear Interpolation) method was employed for the merge, using specific parameter filters for self-attention and MLP (Multi-Layer Perceptron) layers. The configuration includes a set of parameters with different values assigned to the self-attention and MLP filters, operating in the bfloat16 data type.

Guide: Running Locally

1. Clone the Repository: Use Git to clone the model repository from Hugging Face.
2. Install Dependencies: Ensure that the transformers library is installed. You can do this via pip:

   pip install transformers
   

3. Load the Model: Use the transformers library to load the model:

   from transformers import AutoModelForCausalLM, AutoTokenizer
   
   tokenizer = AutoTokenizer.from_pretrained("jaspionjader/Kosmos-EVAA-v9-8B")
   model = AutoModelForCausalLM.from_pretrained("jaspionjader/Kosmos-EVAA-v9-8B")
   

4. Inference: Input text to generate outputs using the model:

   input_text = "Your text here"
   inputs = tokenizer(input_text, return_tensors="pt")
   outputs = model.generate(**inputs)
   print(tokenizer.decode(outputs[0]))
   

5. Consider Cloud GPUs: For performance optimization, particularly for large models like Kosmos-EVAA-v9-8B, consider using cloud-based GPU services such as AWS, Google Cloud, or Azure.

License
The model's license details can be found in the repository on Hugging Face. Ensure compliance with the specified terms when using the model.