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DrNicefellow/
Mistral-2-from-Mixtral-8x7B-v0.1

Name: Mistral-2-from-Mixtral-8x7B-v0.1
Availability: InStock

text-generation-inference

endpoints_compatible

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Mixtral-8x7B--v0.1: Model 2

Model Description

This model is the 2nd extracted standalone model from the mistralai/Mixtral-8x7B-v0.1, using the Mixtral Model Expert Extractor tool I made. It is constructed by selecting the first expert from each Mixture of Experts (MoE) layer. The extraction of this model is experimental. It is expected to be worse than Mistral-7B.

Model Architecture

The architecture of this model includes:

Multi-head attention layers derived from the base Mixtral model.
The first expert from each MoE layer, intended to provide a balanced approach to language understanding and generation tasks.
Additional layers and components as required to ensure the model's functionality outside the MoE framework.

Example

python

from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "DrNicefellow/Mistral-2-from-Mixtral-8x7B-v0.1"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

text = "Today is a pleasant"
input_ids = tokenizer.encode(text, return_tensors='pt')
output = model.generate(input_ids)

print(tokenizer.decode(output[0], skip_special_tokens=True))

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License

This model is open-sourced under the Apache 2.0 License. See the LICENSE file for more details.