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llama.cpp
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convert : handle int-quantized models

This commit is contained in:
Francis Couture-Harpin 2025-11-06 21:11:52 -05:00
parent 33dba6ce02
commit d23bdd57b0
1 changed files with 6 additions and 2 deletions
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8
convert_hf_to_gguf.py
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@ -411,9 +411,11 @@ class ModelBase:
if len(groups) > 1:
raise NotImplementedError("Can't handle multiple config groups for compressed-tensors yet")
weight_config = tuple(groups.values())[0]["weights"]
if quant_format == "float-quantized":
if quant_format == "float-quantized" or quant_format == "int-quantized":
block_size = weight_config.get("block_structure", None)
assert weight_config.get("strategy") == "channel"
strategy = weight_config.get("strategy")
assert strategy == "channel" or strategy == "block"
assert weight_config.get("group_size") == None # didn't find a model using this yet
for name in self.model_tensors.keys():
if name.endswith(".weight_scale"):
@ -444,6 +446,8 @@ class ModelBase:
tensors_to_remove += [base_name + n for n in ("_packed", "_shape", "_scale")]
if (base_name + "_zero_point") in self.model_tensors:
tensors_to_remove.append(base_name + "_zero_point")
else:
raise NotImplementedError(f"Quant format {quant_format!r} for method {quant_method!r} is not yet supported")
else:
raise NotImplementedError(f"Quant method is not yet supported: {quant_method!r}")