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Browse files- .gitattributes +4 -0
- Pythia-Chat-Base-7B.f16.gguf +3 -0
- Pythia-Chat-Base-7B.q5_k.gguf +3 -0
- Pythia-Chat-Base-7B.q6_k.gguf +3 -0
- Pythia-Chat-Base-7B.q8_0.gguf +3 -0
- README.md +14 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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Pythia-Chat-Base-7B.f16.gguf filter=lfs diff=lfs merge=lfs -text
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Pythia-Chat-Base-7B.q5_k.gguf filter=lfs diff=lfs merge=lfs -text
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Pythia-Chat-Base-7B.q6_k.gguf filter=lfs diff=lfs merge=lfs -text
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Pythia-Chat-Base-7B.q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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Pythia-Chat-Base-7B.f16.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:59d1c48a1b980a5a12f39a5c1e24c57c7c643773769217ef420081f88bd14044
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size 13719821408
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Pythia-Chat-Base-7B.q5_k.gguf
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Pythia-Chat-Base-7B.q6_k.gguf
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Pythia-Chat-Base-7B.q8_0.gguf
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README.md
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---
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license: mit
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language:
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- en
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---
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My own (ZeroWw) quantizations.
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output and embed tensors quantized to f16.
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all other tensors quantized to q5_k or q6_k.
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Result:
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both f16.q6 and f16.q5 are smaller than q8_0 standard quantization
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and they perform as well as the pure f16.
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