diff --git a/common/json-schema-to-grammar.cpp b/common/json-schema-to-grammar.cpp
index 4b1401ef1..46c2dc4d7 100644
--- a/common/json-schema-to-grammar.cpp
+++ b/common/json-schema-to-grammar.cpp
@@ -991,7 +991,7 @@ public:
 };
 
 std::string json_schema_to_grammar(const json & schema) {
-#ifdef LLAMA_LLGUIDANCE
+#ifdef LLAMA_USE_LLGUIDANCE
     return "llg:json:" + schema.dump();
 #else
     return build_grammar([&](const llama_grammar_builder & callbacks) {
diff --git a/common/llguidance.cpp b/common/llguidance.cpp
index 4120e93b2..623211747 100644
--- a/common/llguidance.cpp
+++ b/common/llguidance.cpp
@@ -1,8 +1,15 @@
-#ifdef LLAMA_LLGUIDANCE
+#ifdef LLAMA_USE_LLGUIDANCE
+
+#include "common.h"
+#include "sampling.h"
+#include "log.h"
+#include "llama.h"
+
 #include "llguidance.h"
 
 struct llama_sampler_llg {
     const struct llama_model * model;
+    const struct llama_vocab * vocab;
     std::string grammar_kind;
     std::string grammar_data;
     LlgTokenizer *tokenizer;
@@ -17,7 +24,7 @@ static LlgConstraint *llama_sampler_llg_new(LlgTokenizer *tokenizer,
     llg_constraint_init_set_defaults(&cinit, tokenizer);
     auto c = llg_new_constraint_any(&cinit, grammar_kind, grammar_data);
     if (llg_get_error(c)) {
-        LLAMA_LOG_ERROR("llg error: %s\n", llg_get_error(c));
+        LOG_ERR("llg error: %s\n", llg_get_error(c));
         llg_free_constraint(c);
         return nullptr;
     }
@@ -44,7 +51,7 @@ static void llama_sampler_llg_apply(struct llama_sampler * smpl, llama_token_dat
             if (llg_compute_mask(ctx->grammar, &ctx->llg_res) == 0) {
                 ctx->has_llg_res = true;
             } else {
-                LLAMA_LOG_ERROR("llg error: %s\n", llg_get_error(ctx->grammar));
+                LOG_ERR("llg error: %s\n", llg_get_error(ctx->grammar));
                 llg_free_constraint(ctx->grammar);
                 ctx->grammar = nullptr;
             }
@@ -52,7 +59,7 @@ static void llama_sampler_llg_apply(struct llama_sampler * smpl, llama_token_dat
         if (ctx->has_llg_res) {
             if (ctx->llg_res.is_stop) {
                 for (size_t i = 0; i < cur_p->size; ++i) {
-                    if (!llama_token_is_eog(ctx->model, cur_p->data[i].id)) {
+                    if (!llama_vocab_is_eog(ctx->vocab, cur_p->data[i].id)) {
                         cur_p->data[i].logit = -INFINITY;
                     }
                 }
@@ -128,8 +135,8 @@ static size_t llama_sampler_llg_tokenize_fn(const void *user_data,
                                 uint32_t *output_tokens,
                                 size_t output_tokens_len)
 {
-    const struct llama_model *model = (const struct llama_model *)user_data;
-    int r = llama_tokenize(model, (const char *) bytes, bytes_len, 
+    const struct llama_vocab *vocab = (const struct llama_vocab *)user_data;
+    int r = llama_tokenize(vocab, (const char *) bytes, bytes_len, 
         (int32_t*)output_tokens, output_tokens_len, false, true);
     if (r < 0)
         return -r;
@@ -145,11 +152,13 @@ static LlgTokenizer *llama_sampler_llg_new_tokenizer(const struct llama_model *
         return llg_clone_tokenizer(tokenizer_cache);
     }
 
-    auto tok_eos = llama_token_eot(model);
-    if (tok_eos == LLAMA_TOKEN_NULL)
-        tok_eos = llama_token_eos(model);
+    const struct llama_vocab *vocab = llama_model_get_vocab(model);
 
-    size_t vocab_size = llama_n_vocab(model);
+    auto tok_eos = llama_vocab_eot(vocab);
+    if (tok_eos == LLAMA_TOKEN_NULL)
+        tok_eos = llama_vocab_eos(vocab);
+
+    size_t vocab_size = llama_vocab_n_tokens(vocab);
 
     auto token_lens = new uint32_t[vocab_size];
     // we typically have ~7 bytes per token; let's go on the safe side here
@@ -165,12 +174,12 @@ static LlgTokenizer *llama_sampler_llg_new_tokenizer(const struct llama_model *
 
         llama_token token = i;
         auto dp = (char *) token_bytes + offset;
-        auto size = llama_detokenize(model, &token, 1, dp, max_token, false, false);
+        auto size = llama_detokenize(vocab, &token, 1, dp, max_token, false, false);
         if (size < 0) {
             GGML_ABORT("llama_detokenize failed\n");
         }
         if (size == 0) {
-            size = llama_detokenize(model, &token, 1, dp + 1, max_token - 1, false, true);
+            size = llama_detokenize(vocab, &token, 1, dp + 1, max_token - 1, false, true);
             if (size < 0) {
                 GGML_ABORT("llama_detokenize failed\n");
             }
@@ -194,7 +203,7 @@ static LlgTokenizer *llama_sampler_llg_new_tokenizer(const struct llama_model *
         /* .tokenize_assumes_string            = */ false,
         /* .tokenize_fn                        = */ llama_sampler_llg_tokenize_fn,
         /* .use_approximate_greedy_tokenize_fn = */ false,
-        /* .tokenize_user_data                 = */ model,
+        /* .tokenize_user_data                 = */ vocab,
     };
 
     char error_buffer[1024];
@@ -204,7 +213,7 @@ static LlgTokenizer *llama_sampler_llg_new_tokenizer(const struct llama_model *
     delete[] token_lens;
 
     if (tokenizer == nullptr) {
-        LLAMA_LOG_ERROR("llg tokenizer error: %s\n", error_buffer);
+        LOG_ERR("llg tokenizer error: %s\n", error_buffer);
         return tokenizer;
     }
 
@@ -221,10 +230,13 @@ struct llama_sampler * llama_sampler_init_llg(const struct llama_model * model,
         const char * grammar_kind, const char * grammar_data) {
     auto * ctx = new llama_sampler_llg;
 
+    const llama_vocab * vocab = llama_model_get_vocab(model);
+
     if (grammar_kind != nullptr && grammar_kind[0] != '\0') {
         auto tokenizer = llama_sampler_llg_new_tokenizer(model);
         *ctx = {
             /* .model        = */ model,
+            /* .vocab        = */ vocab,
             /* .grammar_kind = */ grammar_kind,
             /* .grammar_data = */ grammar_data,
             /* .tokenizer    = */ tokenizer,
@@ -235,6 +247,7 @@ struct llama_sampler * llama_sampler_init_llg(const struct llama_model * model,
     } else {
         *ctx = {
             /* .model        = */ model,
+            /* .vocab        = */ vocab,
             /* .grammar_kind = */ {},
             /* .grammar_data = */ {},
             /* .tokenizer    = */ nullptr,
diff --git a/common/sampling.cpp b/common/sampling.cpp
index e12301bc4..97691c04b 100644
--- a/common/sampling.cpp
+++ b/common/sampling.cpp
@@ -153,7 +153,7 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co
 
     struct llama_sampler * grmr;
     if (params.grammar.compare(0, 4, "llg:") == 0) {
-#ifdef LLAMA_LLGUIDANCE
+#ifdef LLAMA_USE_LLGUIDANCE
         auto gp = params.grammar.find(':', 4);
         if (gp == std::string::npos) {
             GGML_ABORT("invalid serialized grammar");
@@ -162,7 +162,7 @@ struct common_sampler * common_sampler_init(const struct llama_model * model, co
         auto grm_data = params.grammar.c_str() + gp + 1;
         grmr = llama_sampler_init_llg(model, grm_type.c_str(), grm_data);
 #else
-        GGML_ABORT("llguidance (LLAMA_LLGUIDANCE cmake parameter) is not enabled");
+        GGML_ABORT("llguidance (cmake -DLLAMA_LLGUIDANCE=ON) is not enabled");
 #endif
     } else {
         grmr = llama_sampler_init_grammar(vocab, params.grammar.c_str(), "root");
diff --git a/common/sampling.h b/common/sampling.h
index 348911b18..59baee133 100644
--- a/common/sampling.h
+++ b/common/sampling.h
@@ -102,3 +102,8 @@ std::string common_sampler_type_to_str(enum common_sampler_type cnstr);
 
 std::vector<enum common_sampler_type> common_sampler_types_from_names(const std::vector<std::string> & names, bool allow_alt_names);
 std::vector<enum common_sampler_type> common_sampler_types_from_chars(const std::string & chars);
+
+#ifdef LLAMA_USE_LLGUIDANCE
+struct llama_sampler * llama_sampler_init_llg(const struct llama_model * model, 
+        const char * grammar_kind, const char * grammar_data);
+#endif
\ No newline at end of file