43 lines
1.5 KiB
Go
43 lines
1.5 KiB
Go
package convert
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import (
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"github.com/ollama/ollama/llm"
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)
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type gemma2Model struct {
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gemmaModel
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SlidingWindow uint32 `json:"sliding_window"`
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AttentionLogitSoftcap float32 `json:"attn_logit_softcapping"`
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FinalLogitSoftcap float32 `json:"final_logit_softcapping"`
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}
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func (p *gemma2Model) KV(t *Tokenizer) llm.KV {
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kv := p.ModelParameters.KV(t)
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kv["general.architecture"] = "gemma2"
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kv["gemma2.context_length"] = p.MaxPositionEmbeddings
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kv["gemma2.embedding_length"] = p.HiddenSize
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kv["gemma2.block_count"] = p.HiddenLayers
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kv["gemma2.feed_forward_length"] = p.IntermediateSize
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kv["gemma2.attention.head_count"] = p.NumAttentionHeads
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kv["gemma2.attention.head_count_kv"] = p.NumKeyValueHeads
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kv["gemma2.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
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kv["gemma2.attention.key_length"] = p.HeadDim
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kv["gemma2.attention.value_length"] = p.HeadDim
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kv["gemma2.attention.sliding_window"] = p.SlidingWindow
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kv["gemma2.attn_logit_softcapping"] = p.AttentionLogitSoftcap
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kv["gemma2.final_logit_softcapping"] = p.FinalLogitSoftcap
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kv["tokenizer.ggml.eot_token_id"] = uint32(107)
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kv["tokenizer.ggml.middle_token_id"] = uint32(68)
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kv["tokenizer.ggml.prefix_token_id"] = uint32(67)
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kv["tokenizer.ggml.suffix_token_id"] = uint32(69)
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return kv
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}
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func (p *gemma2Model) Replacements() []string {
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return append(
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p.gemmaModel.Replacements(),
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"post_attention_layernorm", "post_attention_norm",
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"pre_feedforward_layernorm", "ffn_norm",
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"post_feedforward_layernorm", "post_ffw_norm",
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)
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}
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