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feat(convert_hf_to_gguf): support q4_0 and q4_1 quantifications #10008

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feat(convert_hf_to_gguf): support q4_0 and q4_1 quantifications #10008

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10 changes: 8 additions & 2 deletions convert_hf_to_gguf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -357,6 +357,10 @@ def prepare_tensors(self):
data_qtype = gguf.GGMLQuantizationType.TQ1_0
elif self.ftype == gguf.LlamaFileType.MOSTLY_TQ2_0:
data_qtype = gguf.GGMLQuantizationType.TQ2_0
elif self.ftype == gguf.LlamaFileType.MOSTLY_Q4_0:
data_qtype = gguf.GGMLQuantizationType.Q4_0
elif self.ftype == gguf.LlamaFileType.MOSTLY_Q4_1:
data_qtype = gguf.GGMLQuantizationType.Q4_1
else:
raise ValueError(f"Unknown file type: {self.ftype.name}")

Expand Down Expand Up @@ -4293,8 +4297,8 @@ def parse_args() -> argparse.Namespace:
help="path to write to; default: based on input. {ftype} will be replaced by the outtype.",
)
parser.add_argument(
"--outtype", type=str, choices=["f32", "f16", "bf16", "q8_0", "tq1_0", "tq2_0", "auto"], default="f16",
help="output format - use f32 for float32, f16 for float16, bf16 for bfloat16, q8_0 for Q8_0, tq1_0 or tq2_0 for ternary, and auto for the highest-fidelity 16-bit float type depending on the first loaded tensor type",
"--outtype", type=str, choices=["f32", "f16", "bf16", "q4_0", "q4_1", "q8_0", "tq1_0", "tq2_0", "auto"], default="f16",
help="output format - use f32 for float32, f16 for float16, bf16 for bfloat16, q4_0, q4_1 , q8_0 for Q8_0, tq1_0 or tq2_0 for ternary, and auto for the highest-fidelity 16-bit float type depending on the first loaded tensor type",
)
parser.add_argument(
"--bigendian", action="store_true",
Expand Down Expand Up @@ -4380,6 +4384,8 @@ def main() -> None:
"f32": gguf.LlamaFileType.ALL_F32,
"f16": gguf.LlamaFileType.MOSTLY_F16,
"bf16": gguf.LlamaFileType.MOSTLY_BF16,
"q4_0": gguf.LlamaFileType.MOSTLY_Q4_0,
"q4_1": gguf.LlamaFileType.MOSTLY_Q4_1,
"q8_0": gguf.LlamaFileType.MOSTLY_Q8_0,
"tq1_0": gguf.LlamaFileType.MOSTLY_TQ1_0,
"tq2_0": gguf.LlamaFileType.MOSTLY_TQ2_0,
Expand Down