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

huggingface.co
Total runs: 24
24-hour runs: 0
7-day runs: 1
30-day runs: 12
Model's Last Updated: April 26 2024
text-generation

Introduction of Mistral-2-from-Mixtral-8x7B-v0.1

Model Details of Mistral-2-from-Mixtral-8x7B-v0.1

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
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.

Runs of DrNicefellow Mistral-2-from-Mixtral-8x7B-v0.1 on huggingface.co

24
Total runs
0
24-hour runs
2
3-day runs
1
7-day runs
12
30-day runs

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Mistral-2-from-Mixtral-8x7B-v0.1 install

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