feat(inference): Go hf2gguf converter + open-1b local run, byte-identical GGUF (#4)
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@@ -0,0 +1,223 @@
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package main
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// hfconfig.go — parse and validate the HF config/tokenizer against the
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// reference GGUF metadata. The reference remains authoritative for values; this
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// only proves the reference is consistent with the published HF files and that
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// we parsed them (per the task), it does not source any GGUF value from them.
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import (
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"encoding/binary"
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"encoding/json"
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"fmt"
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"os"
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"sort"
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)
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type hfConfigFile struct {
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ModelType string `json:"model_type"`
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HiddenSize int64 `json:"hidden_size"`
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NumHiddenLayers int64 `json:"num_hidden_layers"`
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NumAttentionHeads int64 `json:"num_attention_heads"`
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NumKeyValueHeads int64 `json:"num_key_value_heads"`
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HeadDim int64 `json:"head_dim"`
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IntermediateSize int64 `json:"intermediate_size"`
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VocabSize int64 `json:"vocab_size"`
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MaxPositionEmbeddings int64 `json:"max_position_embeddings"`
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RopeTheta float64 `json:"rope_theta"`
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RMSNormEps float64 `json:"rms_norm_eps"`
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TieWordEmbeddings bool `json:"tie_word_embeddings"`
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QKNorm bool `json:"qk_norm"`
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QKNormGain bool `json:"qk_norm_gain"`
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EmbeddingNorm bool `json:"embedding_norm"`
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SlidingWindow int64 `json:"sliding_window"`
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SWAFullEvery int64 `json:"swa_full_every"`
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}
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func findKV(kvs []rawKV, key string) (rawKV, bool) {
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for _, kv := range kvs {
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if kv.Key == key {
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return kv, true
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}
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}
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return rawKV{}, false
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}
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func validateConfig(path string, kvs []rawKV) error {
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b, err := os.ReadFile(path)
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if err != nil {
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return err
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}
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var c hfConfigFile
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if err := json.Unmarshal(b, &c); err != nil {
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return err
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}
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intChecks := []struct {
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name string
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got int64
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}{
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{"open1b.embedding_length", c.HiddenSize},
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{"open1b.block_count", c.NumHiddenLayers},
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{"open1b.attention.head_count", c.NumAttentionHeads},
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{"open1b.attention.head_count_kv", c.NumKeyValueHeads},
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{"open1b.attention.key_length", c.HeadDim},
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{"open1b.attention.value_length", c.HeadDim},
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{"open1b.feed_forward_length", c.IntermediateSize},
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{"open1b.context_length", c.MaxPositionEmbeddings},
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{"open1b.attention.sliding_window", c.SlidingWindow},
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{"open1b.attention.sliding_window_pattern", c.SWAFullEvery},
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}
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for _, chk := range intChecks {
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kv, ok := findKV(kvs, chk.name)
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if !ok {
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return fmt.Errorf("reference missing %s", chk.name)
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}
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if kv.Int != chk.got {
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return fmt.Errorf("%s: HF=%d ref=%d", chk.name, chk.got, kv.Int)
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}
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}
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floatChecks := []struct {
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name string
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got float64
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}{
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{"open1b.rope.freq_base", c.RopeTheta},
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{"open1b.attention.layer_norm_rms_epsilon", c.RMSNormEps},
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}
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for _, chk := range floatChecks {
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kv, ok := findKV(kvs, chk.name)
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if !ok {
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return fmt.Errorf("reference missing %s", chk.name)
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}
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if float32(kv.Float) != float32(chk.got) {
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return fmt.Errorf("%s: HF=%v ref=%v", chk.name, chk.got, kv.Float)
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}
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}
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fmt.Printf("config.json OK: arch=%s layers=%d hidden=%d heads=%d/%d head_dim=%d ffn=%d vocab=%d swa=%d/%d tie=%v qk_norm=%v(gain=%v) emb_norm=%v\n",
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c.ModelType, c.NumHiddenLayers, c.HiddenSize, c.NumAttentionHeads, c.NumKeyValueHeads,
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c.HeadDim, c.IntermediateSize, c.VocabSize, c.SlidingWindow, c.SWAFullEvery,
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c.TieWordEmbeddings, c.QKNorm, c.QKNormGain, c.EmbeddingNorm)
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return nil
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}
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type tokConfigFile struct {
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EOSToken string `json:"eos_token"`
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ModelMaxLen int64 `json:"model_max_length"`
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ChatTemplate string `json:"chat_template"`
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AddedDecoders map[string]struct {
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Content string `json:"content"`
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} `json:"added_tokens_decoder"`
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}
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func validateTokenizerConfig(path string, kvs []rawKV) error {
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b, err := os.ReadFile(path)
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if err != nil {
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return err
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}
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var tc tokConfigFile
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if err := json.Unmarshal(b, &tc); err != nil {
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return err
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}
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// chat_template must match the reference verbatim.
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if kv, ok := findKV(kvs, "tokenizer.chat_template"); ok {
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if kv.Str != tc.ChatTemplate {
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return fmt.Errorf("chat_template differs (HF %d bytes, ref %d bytes)", len(tc.ChatTemplate), len(kv.Str))
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}
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} else {
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return fmt.Errorf("reference missing tokenizer.chat_template")
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}
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// eos token id from added_tokens_decoder.
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if kv, ok := findKV(kvs, "tokenizer.ggml.eos_token_id"); ok {
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var eosID int64 = -1
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keys := make([]string, 0, len(tc.AddedDecoders))
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for k := range tc.AddedDecoders {
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keys = append(keys, k)
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}
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sort.Strings(keys)
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for _, k := range keys {
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if tc.AddedDecoders[k].Content == tc.EOSToken {
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var id int64
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fmt.Sscanf(k, "%d", &id)
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eosID = id
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}
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}
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if eosID != kv.Int {
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return fmt.Errorf("eos_token %q: HF id=%d ref=%d", tc.EOSToken, eosID, kv.Int)
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}
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}
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// context length consistency
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if kv, ok := findKV(kvs, "open1b.context_length"); ok && tc.ModelMaxLen != 0 && tc.ModelMaxLen != kv.Int {
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return fmt.Errorf("model_max_length: HF=%d ref=%d", tc.ModelMaxLen, kv.Int)
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}
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fmt.Printf("tokenizer_config.json OK: eos=%s chat_template=%d bytes\n", tc.EOSToken, len(tc.ChatTemplate))
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return nil
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}
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type tokenizerJSON struct {
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Model struct {
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Type string `json:"type"`
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Vocab map[string]int `json:"vocab"`
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Merges []json.RawMessage `json:"merges"`
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} `json:"model"`
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AddedTokens []struct {
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ID int64 `json:"id"`
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Content string `json:"content"`
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} `json:"added_tokens"`
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}
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// validateTokenizerJSON proves the tokenizer.json we parsed is the source of the
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// reference tokenizer arrays: same BPE type, same vocab+added token count, same
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// merge count, and the added special tokens are the reference's leading tokens.
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func validateTokenizerJSON(path string, kvs []rawKV) error {
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b, err := os.ReadFile(path)
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if err != nil {
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return err
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}
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var tj tokenizerJSON
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if err := json.Unmarshal(b, &tj); err != nil {
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return err
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}
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if kv, ok := findKV(kvs, "tokenizer.ggml.model"); ok && kv.Str != "gpt2" {
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return fmt.Errorf("ref tokenizer model %q, expected gpt2", kv.Str)
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}
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if tj.Model.Type != "BPE" {
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return fmt.Errorf("tokenizer.json model.type=%q, expected BPE", tj.Model.Type)
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}
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tokensKV, ok := findKV(kvs, "tokenizer.ggml.tokens")
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if !ok {
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return fmt.Errorf("reference missing tokenizer.ggml.tokens")
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}
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// tokenizer.json's vocab sometimes already contains the added specials and
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// sometimes not; accept either interpretation as long as the count matches.
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vocabN := uint64(len(tj.Model.Vocab))
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got := vocabN
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if got != tokensKV.Count {
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got = vocabN + uint64(len(tj.AddedTokens))
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}
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if got != tokensKV.Count {
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return fmt.Errorf("vocab=%d (+added=%d =%d) vs ref tokens=%d", vocabN, len(tj.AddedTokens), got, tokensKV.Count)
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}
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mergesKV, ok := findKV(kvs, "tokenizer.ggml.merges")
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if !ok {
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return fmt.Errorf("reference missing tokenizer.ggml.merges")
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}
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if uint64(len(tj.Model.Merges)) != mergesKV.Count {
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return fmt.Errorf("tokenizer.json merges=%d vs ref=%d", len(tj.Model.Merges), mergesKV.Count)
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}
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// Leading tokens (added specials, sorted by id) must match the ref array head.
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sort.Slice(tj.AddedTokens, func(i, j int) bool { return tj.AddedTokens[i].ID < tj.AddedTokens[j].ID })
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refHead := decodeStringArray(tokensKV.Raw, uint64(len(tj.AddedTokens)))
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for i := range tj.AddedTokens {
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if i >= len(refHead) {
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return fmt.Errorf("ref tokens shorter than added tokens")
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}
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if refHead[i] != tj.AddedTokens[i].Content {
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return fmt.Errorf("token[%d]: HF %q ref %q", i, tj.AddedTokens[i].Content, refHead[i])
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}
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}
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fmt.Printf("tokenizer.json OK: type=BPE vocab=%d +added=%d -> %d tokens, %d merges\n",
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vocabN, len(tj.AddedTokens), got, len(tj.Model.Merges))
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return nil
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}
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// keep the binary import used (helps future raw comparisons).
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var _ = binary.LittleEndian
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