Merge pull request #5443 from ollama/mxyng/convert-phi3
add conversion for microsoft phi 3 mini/medium 4k, 128k
This commit is contained in:
Michael Yang
GitHub
commit
01b80e9ffc
8 changed files with 375 additions and 12 deletions
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@ -27,6 +27,10 @@ func (Parameters) KV(t *Tokenizer) llm.KV {
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"tokenizer.ggml.token_type": t.Vocabulary.Types,
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"tokenizer.ggml.token_type": t.Vocabulary.Types,
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}
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}
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if len(t.Merges) > 0 {
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kv["tokenizer.ggml.merges"] = t.Merges
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}
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if t.Template != "" {
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if t.Template != "" {
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kv["tokenizer.chat_template"] = t.Template
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kv["tokenizer.chat_template"] = t.Template
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}
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}
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@ -89,6 +93,8 @@ func Convert(fsys fs.FS, ws io.WriteSeeker) error {
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conv = &mixtral{}
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conv = &mixtral{}
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case "GemmaForCausalLM":
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case "GemmaForCausalLM":
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conv = &gemma{}
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conv = &gemma{}
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case "Phi3ForCausalLM":
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conv = &phi3{}
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default:
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default:
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return errors.New("unsupported architecture")
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return errors.New("unsupported architecture")
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}
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}
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@ -90,10 +90,6 @@ func (p *llama) KV(t *Tokenizer) llm.KV {
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kv["llama.attention.value_length"] = p.HeadDim
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kv["llama.attention.value_length"] = p.HeadDim
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}
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}
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if len(t.Merges) > 0 {
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kv["tokenizer.ggml.merges"] = t.Merges
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}
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return kv
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return kv
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}
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}
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125
convert/convert_phi3.go
Normal file
125
convert/convert_phi3.go
Normal file
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@ -0,0 +1,125 @@
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package convert
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import (
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"cmp"
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"encoding/binary"
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"io"
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"math"
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"strings"
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"sync"
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"github.com/ollama/ollama/llm"
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)
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type phi3 struct {
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Parameters
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NumHiddenLayers uint32 `json:"num_hidden_layers"`
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NLayers uint32 `json:"n_layers"`
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HiddenSize uint32 `json:"hidden_size"`
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NEmbd uint32 `json:"n_embd"`
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IntermediateSize uint32 `json:"intermediate_size"`
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NumAttentionHeads uint32 `json:"num_attention_heads"`
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NHead uint32 `json:"n_head"`
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NumKeyValueHeads uint32 `json:"num_key_value_heads"`
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NHeadKV uint32 `json:"n_head_kv"`
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RopeTheta float32 `json:"rope_theta"`
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RopeScaling struct {
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Type string `json:"type"`
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LongFactor ropeFactor `json:"long_factor"`
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ShortFactor ropeFactor `json:"short_factor"`
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} `json:"rope_scaling"`
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RMSNormEPS float32 `json:"rms_norm_eps"`
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NPositions uint32 `json:"n_positions"`
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MaxPositionEmbeddings uint32 `json:"max_position_embeddings"`
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OriginalMaxPositionEmbeddings uint32 `json:"original_max_position_embeddings"`
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SlidingWindow uint32 `json:"sliding_window"`
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}
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var _ Converter = (*phi3)(nil)
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func (p *phi3) KV(t *Tokenizer) llm.KV {
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kv := p.Parameters.KV(t)
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kv["general.architecture"] = "phi3"
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kv["general.name"] = "phi3"
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kv["phi3.context_length"] = p.MaxPositionEmbeddings
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kv["phi3.embedding_length"] = cmp.Or(p.HiddenSize, p.NEmbd)
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kv["phi3.feed_forward_length"] = p.IntermediateSize
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kv["phi3.block_count"] = cmp.Or(p.NumHiddenLayers, p.NLayers)
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kv["phi3.attention.head_count"] = cmp.Or(p.NumAttentionHeads, p.NHead)
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kv["phi3.attention.head_count_kv"] = cmp.Or(p.NumKeyValueHeads, p.NHeadKV)
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kv["phi3.attention.layer_norm_rms_epsilon"] = p.RMSNormEPS
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kv["phi3.rope.dimension_count"] = p.HiddenSize / cmp.Or(p.NumAttentionHeads, p.NHead)
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kv["phi3.rope.freq_base"] = p.RopeTheta
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kv["phi3.rope.scaling.original_context_length"] = p.OriginalMaxPositionEmbeddings
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kv["phi3.attention.sliding_window"] = p.SlidingWindow
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scale := float64(p.MaxPositionEmbeddings) / float64(p.OriginalMaxPositionEmbeddings)
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switch p.RopeScaling.Type {
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case "":
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// no scaling
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case "su", "longrope":
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kv["phi3.rope.scaling.attn_factor"] = float32(max(math.Sqrt(1+math.Log(scale)/math.Log(float64(p.OriginalMaxPositionEmbeddings))), 1.0))
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case "yarn":
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kv["phi3.rope.scaling.attn_factor"] = float32(max(0.1*math.Log(scale)+1.0, 1.0))
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default:
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panic("unknown rope scaling type")
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}
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return kv
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}
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func (p *phi3) Tensors(ts []Tensor) []llm.Tensor {
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var addRopeFactors sync.Once
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out := make([]llm.Tensor, 0, len(ts)+2)
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for _, t := range ts {
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name := p.tensorName(t.Name())
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if strings.HasPrefix(name, "blk.0.") {
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addRopeFactors.Do(func() {
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out = append(out, llm.Tensor{
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Name: "rope_factors_long.weight",
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Kind: 0,
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Shape: []uint64{uint64(len(p.RopeScaling.LongFactor))},
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WriterTo: p.RopeScaling.LongFactor,
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}, llm.Tensor{
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Name: "rope_factors_short.weight",
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Kind: 0,
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Shape: []uint64{uint64(len(p.RopeScaling.ShortFactor))},
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WriterTo: p.RopeScaling.ShortFactor,
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})
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})
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}
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out = append(out, llm.Tensor{
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Name: name,
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Kind: t.Kind(),
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Shape: t.Shape(),
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WriterTo: t,
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})
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}
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return out
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}
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func (p *phi3) tensorName(n string) string {
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return strings.NewReplacer(
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"lm_head", "output",
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"model.embed_tokens", "token_embd",
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"model.norm", "output_norm",
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"model.layers", "blk",
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"input_layernorm", "attn_norm",
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"self_attn.qkv_proj", "attn_qkv",
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"self_attn.o_proj", "attn_output",
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"mlp.down_proj", "ffn_down",
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"mlp.gate_up_proj", "ffn_up",
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"post_attention_layernorm", "ffn_norm",
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).Replace(n)
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}
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type ropeFactor []float32
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func (r ropeFactor) WriteTo(w io.Writer) (int64, error) {
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err := binary.Write(w, binary.LittleEndian, r)
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return 0, err
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}
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@ -65,6 +65,8 @@ func TestConvertFull(t *testing.T) {
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"Mistral-7B-Instruct-v0.2",
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"Mistral-7B-Instruct-v0.2",
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"Mixtral-8x7B-Instruct-v0.1",
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"Mixtral-8x7B-Instruct-v0.1",
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"gemma-2b-it",
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"gemma-2b-it",
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// microsoft/Phi-3-mini-128-instruct@d548c233192db00165d842bf8edff054bb3212f8
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"Phi-3-mini-128k-instruct",
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}
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}
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for i := range cases {
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for i := range cases {
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225
convert/testdata/Phi-3-mini-128k-instruct.json
vendored
Normal file
225
convert/testdata/Phi-3-mini-128k-instruct.json
vendored
Normal file
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@ -0,0 +1,225 @@
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{
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"general.architecture": "phi3",
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"general.file_type": "1",
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"general.quantization_version": "2",
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"phi3.block_count": "32",
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"phi3.context_length": "131072",
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"phi3.embedding_length": "3072",
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"phi3.feed_forward_length": "8192",
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"phi3.rope.scaling.original_context_length": "4096",
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"phi3.rope.dimension_count": "96",
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"phi3.rope.freq_base": "10000",
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"phi3.rope.scaling.attn_factor": "1.1902381",
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"phi3.attention.head_count": "32",
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"phi3.attention.head_count_kv": "32",
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"phi3.attention.layer_norm_rms_epsilon": "1e-05",
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"phi3.attention.sliding_window": "262144",
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"tokenizer.ggml.model": "llama",
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"tokenizer.ggml.pre": "default",
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"tokenizer.ggml.add_bos_token": "false",
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"tokenizer.ggml.add_eos_token": "false",
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"tokenizer.ggml.bos_token_id": "1",
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"tokenizer.ggml.eos_token_id": "32000",
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"tokenizer.ggml.unknown_token_id": "0",
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"tokenizer.ggml.padding_token_id": "32000",
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"tokenizer.ggml.scores": "6e37bcde2adc7e350e87c496eddd7a2124329c1dc66c5bf3ad3997253e4f7a62",
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"tokenizer.ggml.token_type": "b6ecf55ec64ee67d87750bdb8d757a2c58bf78377e9f4219f5689a6c4dea57ce",
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"tokenizer.ggml.tokens": "d168da3ddd3eee820916945fcb9baf24dd3cde42f606cffa2d19e7c8a8743918",
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"blk.0.attn_norm.weight": "216aeb2c9e0c271f899e1ef2a63cceeb8f41e97642e84fada54b1d3c1c11cf25",
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"blk.0.attn_output.weight": "b597d56f7188ffc1fafc273fadc59d41738cffd677ae98c61a62c3285b3a3099",
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"blk.0.attn_qkv.weight": "d28a6b44e13f59be5483e4be2bedb544e346168d720aca27f47d1a5a722be91e",
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"blk.0.ffn_down.weight": "4a691370e5a61fcbbf540fbcbf4c0f1d15dec0364528c0e916d0744f6262b63b",
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"blk.0.ffn_norm.weight": "0c00af2b4a3128bec64a0cbb1084b042fdbe13d9ad0d03bd577f9449dfead338",
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"blk.0.ffn_up.weight": "b32b52f790c1c083bfb8a3126dc1111cfeeb28dc8c584a930a1e5334cb176bf4",
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"blk.1.attn_norm.weight": "68748011503c6c029e8e69a84a8e5a89338f378769627b6dbf7f93d715c292e1",
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"blk.1.attn_output.weight": "2267344add13b048ca59e4377c86dc512be8046a57156901fa32a20fa74e4ee0",
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"blk.1.attn_qkv.weight": "9109d2e3d7a2eacfda5226587b8be124a3bf44b972da7ebb17aa15795897eacc",
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"blk.1.ffn_down.weight": "d675df4df4dd039c0c339ad6445d39eddd2004db6bf35bed6314c7497245a633",
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"blk.1.ffn_norm.weight": "3b5767ae977bc8baaa06b06efdbea193b6b3ba605ce76d77a76ce317e935500c",
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"blk.1.ffn_up.weight": "80dfd6d9d234b00334c89b8e0a02f81899c2efd377321c34ba5ba51a5f61b5ff",
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"blk.2.attn_norm.weight": "6a6743b057e5088f145bc179e92c9bfb41163e7295d7b81c62e23dd89d2b59c4",
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"blk.2.attn_output.weight": "bc5491ea54e0db81462d7d9b7d25cbdda380c2db8de041bd1c4ab7b76a1d19c3",
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"blk.2.attn_qkv.weight": "a61287a9852e2f5aca9c100b471d98398b2913a3497c743de3c70ec9ddd7087f",
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"blk.2.ffn_down.weight": "4fddcc382c8dceeab027fe43d8d44e67edb5e8ce4b9a1b7f773c87770380ade1",
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"blk.2.ffn_norm.weight": "07e05f82b3f63f711db3b684ca79aed25c0657917e66f88af47348a82065c227",
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"blk.2.ffn_up.weight": "4835a682ef1826c12df01ae7663fc45f9c82bc8e64b665f13fb7da8e201ec0fb",
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"blk.3.attn_norm.weight": "f22aba7c03999ba7136f39cda747a39715e498699dc1716cd97fc5dfc58d1b1c",
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"blk.3.attn_output.weight": "53b579855366fd786c5126b2b30aac4d583ca7bda56833c4865f5cadb5c18c6d",
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"blk.3.attn_qkv.weight": "bb56aba78158123140fcea59c69ac562ca208f6d3086819417cdad8c50f333ad",
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"blk.3.ffn_down.weight": "97280897a7cd86db2830c004bccc5bc094f50e293baded0189159a2019145a6e",
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"blk.3.ffn_norm.weight": "10a8c99f8b57a960e8e0a1133c4a26f9148403d1b9bff2eff114917de996f3b5",
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"blk.3.ffn_up.weight": "7324046c915e75d621b2043597a245a428d8eea31869135e6257a861491d8dcc",
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|
"blk.4.attn_norm.weight": "507d8e164de94646edbfe33def8e8fbf7c9a6ee3fbaedb5000f72d9f51ec5e36",
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"blk.4.attn_output.weight": "bbb3429e6efa98c150e0fdbf48c16180cbf0d0cbc1b3c253c6c319d78f4593a2",
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"blk.4.attn_qkv.weight": "b95ee5be0786d3901273d806c339fe6c20e6bfffd2a20672a9f56af80921e8ab",
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||||||
|
"blk.4.ffn_down.weight": "806bbf91df92a5a22bd5aa1ffb7fc2869f7293ffc7704771c290ecc583b27975",
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||||||
|
"blk.4.ffn_norm.weight": "cfc2930a81df7aee3a5e7f726a15c1182233e868bf0d9d37f6b6ae6d8c15c234",
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||||||
|
"blk.4.ffn_up.weight": "c3390c69533de2c8424e8069323ccc5d0c4543111535da04cf2c7d26745576aa",
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||||||
|
"blk.5.attn_norm.weight": "0d71c4fbcefabbd021569442853d2fe90668b19409ae2805a718a829ca60beab",
|
||||||
|
"blk.5.attn_output.weight": "10ebd93629112bf2df5c30dd0953a4a5e9020306768283181ed426934d47e14f",
|
||||||
|
"blk.5.attn_qkv.weight": "5cb05633369f12d4b00e0ff787736bd846856682115720ebc6cce05270c334f6",
|
||||||
|
"blk.5.ffn_down.weight": "e28bcc5094212eafc7476dbc5b7a520d25b79578cbf4229d698e2655956a80ad",
|
||||||
|
"blk.5.ffn_norm.weight": "b6f2c4cf9f34bb4d59989f96165c14a67dc1e266ad0a6d0fcc49f1add929e6ff",
|
||||||
|
"blk.5.ffn_up.weight": "0f9ef99423cc07ebedc0e9cfa95809f2d7108d910bb4ef97ebc0b0309c440750",
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||||||
|
"blk.6.attn_norm.weight": "b3edcc47a42218234f7564d7470611b49401a41ae8cd42123f86557c69f5d7f2",
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||||||
|
"blk.6.attn_output.weight": "eb9b7d257b388bb5b8fe0515e5c6873317239cb94cda236e4b6ada2a6c57c65c",
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||||||
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"blk.6.attn_qkv.weight": "eb968081f478c52f07bd9c2761741e982dba33cc4eeadeea3557d391b9ac2106",
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||||||
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"blk.6.ffn_down.weight": "1b8588bb7463206290322695577dcfced300895d6e6f4b26966c53a9ae2f0f84",
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||||||
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"blk.6.ffn_norm.weight": "1219c04b7770983c77814200eefe743f46d15328ea2b12711e44f8103eab08d3",
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||||||
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"blk.6.ffn_up.weight": "197ef287239fec47c55677f0fbb66eaf0644f775bc382de843971730721394f6",
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"blk.7.attn_norm.weight": "b630ad08c80d564ed1c024384818e9fd3f22a36cd7a14aa96e7e2759a8285099",
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||||||
|
"blk.7.attn_output.weight": "970255aa750828a47d6b9d399f9612b5bf25aefe7dadbcba41fc416d0d4067c1",
|
||||||
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"blk.7.attn_qkv.weight": "ebb157c880293e6de8d629f263ba8853ed1dbdc02c311d43432bb8cfbb310739",
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||||||
|
"blk.7.ffn_down.weight": "24bcd4db4cba844c89f878b81843c373dbbc0675e889d32c5b12e63384a7b670",
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||||||
|
"blk.7.ffn_norm.weight": "b9c6f71001808ee873ce7db8056e4b53fb4cccec8b7f0f312899b575fae39d39",
|
||||||
|
"blk.7.ffn_up.weight": "979f1828d227455c26015a2a11afe9dd05f2bb97a8ba6b38c8dab3f50e627401",
|
||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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||||||
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|
||||||
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||||||
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"blk.28.ffn_down.weight": "f1d6e6d1c286b1138bfd7e53fe477f399ae93bc2c04e35416f84218ed7247965",
|
||||||
|
"blk.28.ffn_norm.weight": "3f837ce82c8b9bde0d61d08b6f5fe5574886ea5328dbdc53f2929f18da8b4087",
|
||||||
|
"blk.28.ffn_up.weight": "2af027002e31d1b6cfedbdb30a2b9d7213f3aa691167c353913adfd48fda31e4",
|
||||||
|
"blk.29.attn_norm.weight": "61e8003b5329462ffe0fe172f2b160260de006aed858332d49d75504b6b6aa7a",
|
||||||
|
"blk.29.attn_output.weight": "ca44542a72a37476dc73dbdcc01f5b7497cb3ebc4ea230a55c9634ccd8e56ad4",
|
||||||
|
"blk.29.attn_qkv.weight": "abb3d9d6abe57872ae3daa51935d43264093ded5ce63b49d1e280ee5758be0e4",
|
||||||
|
"blk.29.ffn_down.weight": "6764b895fce881df097489c263446f0106de36217997660c15984b3ee22a5a06",
|
||||||
|
"blk.29.ffn_norm.weight": "89e03e9a33fc0e6e31ba9f0c2bd7c5734a118c5602bb90148793e08a80e8d0ae",
|
||||||
|
"blk.29.ffn_up.weight": "fa7ad57a84954f4121653152efed1a871d8adb20a1ea9086e3e849ce359d7d2e",
|
||||||
|
"blk.30.attn_norm.weight": "91a697aca1e42af54f806a20211031c3369e8d0bd58df1b0147fe24954e1f5a4",
|
||||||
|
"blk.30.attn_output.weight": "36063fcf766c89ac75be56f688cc63cefe5f2c733fbf4378ea9956ad386fa148",
|
||||||
|
"blk.30.attn_qkv.weight": "2cacd1161f1121a2c0b979930134f4666f73fb8d7237b3b0659ae091b15955a6",
|
||||||
|
"blk.30.ffn_down.weight": "9f3fcb6217100595850c05dc98f9ab2a263afdb6ab28df2fcb08aeff512057d7",
|
||||||
|
"blk.30.ffn_norm.weight": "6c600bc1fc7de39d4f8917b81fc7d1d5ed2a9b56492234c13a4bd6028c30d880",
|
||||||
|
"blk.30.ffn_up.weight": "73cabd1bb011956b2689ea3338bb76642ef3a57c197377d666d2ab5f56317668",
|
||||||
|
"blk.31.attn_norm.weight": "72d3e1cc771380645fa75a899858c95f39857a4f3f1ed60fe1578df383b8bc53",
|
||||||
|
"blk.31.attn_output.weight": "40089cdd29994dc19a1d89fa15902a89cfeca3540f12dc9bf4d00ef82506e456",
|
||||||
|
"blk.31.attn_qkv.weight": "1d0bb40e9258071ae14290a53c619a8e331dda07354d2a02ef45766c029ae5e4",
|
||||||
|
"blk.31.ffn_down.weight": "8defa0e06335b793fa8be03883f0a322d6c5b33f52c69c943c35c60d16e42c0a",
|
||||||
|
"blk.31.ffn_norm.weight": "33c55d9d0c496ccfb130361fe131649346e098abaaac39c0519507e5d846721d",
|
||||||
|
"blk.31.ffn_up.weight": "599f6503f61c692c1f82001973d35119f9688db5e6be9d9c298411491c93f09b",
|
||||||
|
"output.weight": "14b8dc662bfa3308ebb2e102c562d8e52c15670e538f20f3216a9c310ca9dd41",
|
||||||
|
"output_norm.weight": "7f2294ba94ce65681df6c7ddd8698799199b9d77dc83c10bdad5c3999f0fdb82",
|
||||||
|
"rope_factors_long.weight": "e34d378664e354652c38f47d10dafb0498ccc2fb042d39ff7fef768146fff22b",
|
||||||
|
"rope_factors_short.weight": "9379146a4988f373d362fe47b06c75e7fe7c54aa4dc9558758df79b7a87471fd",
|
||||||
|
"token_embd.weight": "19a03c1fb5ac0baee93b0a7d8b0f26e9a9b011e229b694afc50ebfc13d84f8bf"
|
||||||
|
}
|
||||||
|
|
@ -16,7 +16,9 @@ If the model being imported is one of these architectures, it can be imported di
|
||||||
|
|
||||||
- LlamaForCausalLM
|
- LlamaForCausalLM
|
||||||
- MistralForCausalLM
|
- MistralForCausalLM
|
||||||
|
- MixtralForCausalLM
|
||||||
- GemmaForCausalLM
|
- GemmaForCausalLM
|
||||||
|
- Phi3ForCausalLM
|
||||||
|
|
||||||
```dockerfile
|
```dockerfile
|
||||||
FROM /path/to/safetensors/directory
|
FROM /path/to/safetensors/directory
|
||||||
|
|
|
||||||
|
|
@ -157,6 +157,14 @@ type Tensor struct {
|
||||||
io.WriterTo `json:"-"`
|
io.WriterTo `json:"-"`
|
||||||
}
|
}
|
||||||
|
|
||||||
|
func (t Tensor) block() (n int) {
|
||||||
|
if _, err := fmt.Sscanf(t.Name, "blk.%d.", &n); err != nil {
|
||||||
|
return -1
|
||||||
|
}
|
||||||
|
|
||||||
|
return
|
||||||
|
}
|
||||||
|
|
||||||
func (t Tensor) blockSize() uint64 {
|
func (t Tensor) blockSize() uint64 {
|
||||||
switch t.Kind {
|
switch t.Kind {
|
||||||
case 0, 1, 24, 25, 26, 27, 28, 30: // F32, F16, I8, I16, I32, I64, F64, BF16
|
case 0, 1, 24, 25, 26, 27, 28, 30: // F32, F16, I8, I16, I32, I64, F64, BF16
|
||||||
|
|
|
||||||
15
llm/gguf.go
15
llm/gguf.go
|
|
@ -532,15 +532,14 @@ func WriteGGUF(ws io.WriteSeeker, kv KV, ts []Tensor) error {
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
slices.SortFunc(ts, func(a, b Tensor) int {
|
slices.SortStableFunc(ts, func(a, b Tensor) int {
|
||||||
var i, j int
|
if i, j := a.block(), b.block(); i < 0 && j > 0 {
|
||||||
if n, err := fmt.Sscanf(a.Name, "blk.%d", &i); err != nil || n != 1 {
|
return 1
|
||||||
return cmp.Compare(a.Name, b.Name)
|
} else if i > 0 && j < 0 {
|
||||||
} else if n, err := fmt.Sscanf(b.Name, "blk.%d", &j); err != nil || n != 1 {
|
return -1
|
||||||
return cmp.Compare(a.Name, b.Name)
|
} else {
|
||||||
|
return cmp.Compare(i, j)
|
||||||
}
|
}
|
||||||
|
|
||||||
return cmp.Compare(i, j)
|
|
||||||
})
|
})
|
||||||
|
|
||||||
var s uint64
|
var s uint64
|
||||||
|
|
|
||||||
Loading…
Reference in a new issue