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Quantization made by Richard Erkhov.

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phi_2 - GGUF

Name Quant method Size
phi_2.Q2_K.gguf Q2_K 1.35GB
phi_2.IQ3_XS.gguf IQ3_XS 1.49GB
phi_2.IQ3_S.gguf IQ3_S 1.57GB
phi_2.Q3_K_S.gguf Q3_K_S 1.57GB
phi_2.IQ3_M.gguf IQ3_M 1.65GB
phi_2.Q3_K.gguf Q3_K 1.75GB
phi_2.Q3_K_M.gguf Q3_K_M 1.75GB
phi_2.Q3_K_L.gguf Q3_K_L 1.9GB
phi_2.IQ4_XS.gguf IQ4_XS 1.93GB
phi_2.Q4_0.gguf Q4_0 2.03GB
phi_2.IQ4_NL.gguf IQ4_NL 2.04GB
phi_2.Q4_K_S.gguf Q4_K_S 2.04GB
phi_2.Q4_K.gguf Q4_K 2.16GB
phi_2.Q4_K_M.gguf Q4_K_M 2.16GB
phi_2.Q4_1.gguf Q4_1 2.24GB
phi_2.Q5_0.gguf Q5_0 2.46GB
phi_2.Q5_K_S.gguf Q5_K_S 2.46GB
phi_2.Q5_K.gguf Q5_K 2.53GB
phi_2.Q5_K_M.gguf Q5_K_M 2.53GB
phi_2.Q5_1.gguf Q5_1 2.68GB
phi_2.Q6_K.gguf Q6_K 2.92GB
phi_2.Q8_0.gguf Q8_0 3.78GB

Original model description:

base_model: unsloth/Phi-3.5-mini-instruct tags: - text-generation-inference - transformers - unsloth - llama - trl - sft license: apache-2.0 language: - en

Uploaded model

  • Developed by: EITD
  • License: apache-2.0
  • Finetuned from model : unsloth/Phi-3.5-mini-instruct

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

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GGUF
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4B params
Architecture
llama
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