address review comments

convert-hf-to-gguf.py

@@ -427,6 +427,9 @@ class Model:
         # NOTE: if you get an error here, you need to update the convert-hf-to-gguf-update.py script
         #       or pull the latest version of the model from Huggingface
         #       don't edit the hashes manually!
+        if chkhsh == "0ef9807a4087ebef797fc749390439009c3b9eda9ad1a097abbe738f486c01e5":
+            # ref: https://huggingface.co/meta-llama/Meta-Llama-3-8B
+            res = "llama-bpe"
         if chkhsh == "049ecf7629871e3041641907f3de7c733e4dbfdc736f57d882ba0b0845599754":
             # ref: https://huggingface.co/deepseek-ai/deepseek-llm-7b-base
             res = "deepseek-llm"
@@ -454,12 +457,18 @@ class Model:
         if chkhsh == "6221ad2852e85ce96f791f476e0b390cf9b474c9e3d1362f53a24a06dc8220ff":
             # ref: https://huggingface.co/smallcloudai/Refact-1_6-base
             res = "refact"
+        if chkhsh == "9c2227e4dd922002fb81bde4fc02b0483ca4f12911410dee2255e4987644e3f8":
+            # ref: https://huggingface.co/CohereForAI/c4ai-command-r-v01
+            res = "command-r"
         if chkhsh == "e636dc30a262dcc0d8c323492e32ae2b70728f4df7dfe9737d9f920a282b8aea":
             # ref: https://huggingface.co/Qwen/Qwen1.5-7B
             res = "qwen2"
         if chkhsh == "b6dc8df998e1cfbdc4eac8243701a65afe638679230920b50d6f17d81c098166":
             # ref: https://huggingface.co/allenai/OLMo-1.7-7B-hf
             res = "olmo"
+        if chkhsh == "a8594e3edff7c29c003940395316294b2c623e09894deebbc65f33f1515df79e":
+            # ref: https://huggingface.co/databricks/dbrx-base
+            res = "dbrx"
         if chkhsh == "0876d13b50744004aa9aeae05e7b0647eac9d801b5ba4668afc01e709c15e19f":
             # ref: https://huggingface.co/jinaai/jina-embeddings-v2-base-en
             res = "jina-v2-en"
@@ -2811,6 +2820,7 @@ class DeepseekV2Model(Model):
             if len(experts) > 0:
                 raise ValueError(f"Unprocessed experts: {experts}")
 
+
 @Model.register("T5ForConditionalGeneration")
 @Model.register("T5WithLMHeadModel")
 class T5Model(Model):

include/llama.h

@@ -652,6 +652,11 @@ extern "C" {
     // State / sessions
     //
 
+    // hack
+    void llama_set_logits_all(
+        struct llama_context * ctx,
+        bool logits_all);
+
     // Returns the maximum size in bytes of the state (rng, logits, embedding
     // and kv_cache) - will often be smaller after compacting tokens
     LLAMA_API size_t llama_state_get_size(const struct llama_context * ctx);

src/llama.cpp

@@ -4281,6 +4281,7 @@ static const char * llama_model_type_name(e_model type) {
         case MODEL_410M:          return "410M";
         case MODEL_0_5B:          return "0.5B";
         case MODEL_1B:            return "1B";
+        case MODEL_1_3B:          return "1.3B";
         case MODEL_1_4B:          return "1.4B";
         case MODEL_2B:            return "2B";
         case MODEL_2_8B:          return "2.8B";
@@ -13105,6 +13106,13 @@ static void llama_graph_compute(
     // fprintf(stderr, "splits: %d\n", ggml_backend_sched_get_n_splits(lctx.sched));
 }
 
+void llama_set_logits_all(
+    struct llama_context * ctx,
+    bool logits_all
+) {
+    ctx->logits_all = logits_all;
+}
+
 // decode a batch of tokens by evaluating the transformer
 //
 //   - lctx:      llama context
@@ -14052,6 +14060,7 @@ struct llm_tokenizer_bpe {
                 break;
             case LLAMA_VOCAB_PRE_TYPE_GPT2:
             case LLAMA_VOCAB_PRE_TYPE_OLMO:
+            case LLAMA_VOCAB_PRE_TYPE_JAIS:
                 regex_exprs = {
                     "'s|'t|'re|'ve|'m|'ll|'d| ?\\p{L}+| ?\\p{N}+| ?[^\\s\\p{L}\\p{N}]+|\\s+(?!\\S)",
                 };