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set head_count_kv = 1
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@ -104,15 +104,11 @@ block_count = hparams["n_layer"]
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gguf_writer.add_name("StarCoder")
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gguf_writer.add_context_length(2048) # not in config.json
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gguf_writer.add_tensor_data_layout("jploski") # qkv tensor transform
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gguf_writer.add_embedding_length(hparams["n_embd"])
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gguf_writer.add_feed_forward_length(4 * hparams["n_embd"])
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gguf_writer.add_block_count(block_count)
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gguf_writer.add_head_count(hparams["n_head"])
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if "n_head_kv" in hparams:
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gguf_writer.add_head_count_kv(hparams["n_head_kv"])
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else:
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gguf_writer.add_head_count_kv(1)
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gguf_writer.add_head_count_kv(1)
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gguf_writer.add_layer_norm_eps(hparams["layer_norm_epsilon"])
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gguf_writer.add_file_type(ftype)
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@ -251,7 +247,7 @@ for part_name in part_names:
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if ftype == 1 and data_dtype == np.float32 and name.endswith(".weight") and n_dims == 2:
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data = data.astype(np.float16)
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print(name, "=>", new_name + ", n_dims = " + str(n_dims) + ", " + str(old_dtype) + " --> " + str(data.dtype))
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print(name, "=>", new_name + ", shape = " + str(data.shape) + ", " + str(old_dtype) + " --> " + str(data.dtype))
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gguf_writer.add_tensor(new_name, data)
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