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xi0v
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Mixtral-test

Text Generation
Transformers
Safetensors
mixtral
mergekit
Merge
text-generation-inference
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How to use from the
Use from the
Transformers library
# Gated model: Login with a HF token with gated access permission
hf auth login
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="xi0v/Mixtral-test")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("xi0v/Mixtral-test")
model = AutoModelForCausalLM.from_pretrained("xi0v/Mixtral-test")
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merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
    - model: macadeliccc/laser-dolphin-mixtral-2x7b-dpo
      layer_range: [0, 24]
  - sources:
    - model: macadeliccc/laser-dolphin-mixtral-2x7b-dpo
      layer_range: [8, 32]
merge_method: passthrough
dtype: float16
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Model size
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Tensor type
F16
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