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py : fix StableLM conversion after config.json changes (#5703)
* Fix issues during StableLM models conversion * Fix hard coded layer_norm_eps * Support layer_norm_eps for LlavaStableLM Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * Add missing parenthesis Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * Support rotary_factor for LlavaStableLM Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> * fix typo * Add StableLMEpochForCausalLM for safety Co-authored-by: compilade <113953597+compilade@users.noreply.github.com> * Add StableLMEpochForCausalLM for safety 2 Co-authored-by: compilade <113953597+compilade@users.noreply.github.com> --------- Co-authored-by: Jared Van Bortel <cebtenzzre@gmail.com> Co-authored-by: Jared Van Bortel <jared@nomic.ai> Co-authored-by: compilade <113953597+compilade@users.noreply.github.com>
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@ -192,7 +192,7 @@ class Model:
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return RefactModel
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if model_architecture == "PersimmonForCausalLM":
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return PersimmonModel
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if model_architecture in ("StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM"):
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if model_architecture in ("StableLmForCausalLM", "StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM"):
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return StableLMModel
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if model_architecture == "QWenLMHeadModel":
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return QwenModel
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@ -253,7 +253,7 @@ class Model:
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return gguf.MODEL_ARCH.REFACT
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if arch == "PersimmonForCausalLM":
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return gguf.MODEL_ARCH.PERSIMMON
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if arch in ("StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM"):
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if arch in ("StableLmForCausalLM", "StableLMEpochForCausalLM", "LlavaStableLMEpochForCausalLM"):
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return gguf.MODEL_ARCH.STABLELM
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if arch == "QWenLMHeadModel":
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return gguf.MODEL_ARCH.QWEN
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@ -1074,10 +1074,11 @@ class StableLMModel(Model):
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self.gguf_writer.add_embedding_length(hparams["hidden_size"])
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self.gguf_writer.add_block_count(block_count)
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self.gguf_writer.add_feed_forward_length(hparams["intermediate_size"])
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self.gguf_writer.add_rope_dimension_count(int(hparams["rope_pct"] * (hparams["hidden_size"] // hparams["num_attention_heads"])))
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rotary_factor = self.find_hparam(["partial_rotary_factor", "rope_pct"])
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self.gguf_writer.add_rope_dimension_count(int(rotary_factor * (hparams["hidden_size"] // hparams["num_attention_heads"])))
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self.gguf_writer.add_head_count(hparams["num_attention_heads"])
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self.gguf_writer.add_parallel_residual(hparams["use_parallel_residual"] if "use_parallel_residual" in hparams else True)
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self.gguf_writer.add_layer_norm_eps(1e-5)
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self.gguf_writer.add_layer_norm_eps(self.find_hparam(["layer_norm_eps", "norm_eps"]))
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class MixtralModel(Model):
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