refactor: Apply model schema to tokenizer downloads

- Add imports for json and hashlib
- Add missing models: phi, stablelm, mistral, and mixtral
- Fix constructor logic
- Fix how models are accessed
- Apply model schema to download_model method

gguf-py/gguf/huggingface_hub.py

@@ -1,7 +1,9 @@
+import json
 import logging
 import os
 import pathlib
 from enum import IntEnum, auto
+from hashlib import sha256
 
 import requests
 from transformers import AutoTokenizer
@@ -42,6 +44,10 @@ MODELS = (
     {"tokt": TokenizerType.WPM, "repo": "jinaai/jina-embeddings-v2-base-en", }, # WPM!
     {"tokt": TokenizerType.BPE, "repo": "jinaai/jina-embeddings-v2-base-es", },
     {"tokt": TokenizerType.BPE, "repo": "jinaai/jina-embeddings-v2-base-de", },
+    {"tokt": TokenizerType.BPE, "repo": "microsoft/phi-1", },
+    {"tokt": TokenizerType.BPE, "repo": "stabilityai/stablelm-2-zephyr-1_6b", },
+    {"tokt": TokenizerType.SPM, "repo": "mistralai/Mistral-7B-Instruct-v0.2", },
+    {"tokt": TokenizerType.SPM, "repo": "mistralai/Mixtral-8x7B-Instruct-v0.1", },
 )
 
 
@@ -103,10 +109,10 @@ class HFTokenizerRequest:
         auth_token: str,
         logger: None | logging.Logger
     ):
-        self._hub = HuggingFaceHub(auth_token, logger)
-
         if dl_path is None:
             self._local_path = pathlib.Path("models/tokenizers")
+        elif isinstance(dl_path, str):
+            self._local_path = pathlib.Path(dl_path)
         else:
             self._local_path = dl_path
 
@@ -116,13 +122,16 @@ class HFTokenizerRequest:
             logger = logging.getLogger("hf-tok-req")
         self.logger = logger
 
+        self._hub = HuggingFaceHub(auth_token, logger)
+        self._models = list(MODELS)
+
     @property
     def hub(self) -> HuggingFaceHub:
         return self._hub
 
     @property
     def models(self) -> list[dict[str, object]]:
-        return MODEL_REPOS
+        return self._models
 
     @property
     def tokenizer_type(self) -> TokenizerType:
@@ -157,12 +166,12 @@ class HFTokenizerRequest:
 
     def download_model(self) -> None:
         for model in self.models:
-            os.makedirs(f"{self.local_path}/{model['name']}", exist_ok=True)
+            os.makedirs(f"{self.local_path}/{model['repo']}", exist_ok=True)
             filenames = self.resolve_filenames(model['tokt'])
             for filename in filenames:
-                filepath = pathlib.Path(f"{self.local_path}/{model['name']}/{filename}")
+                filepath = pathlib.Path(f"{self.local_path}/{model['repo']}/{filename}")
                 if filepath.is_file():
-                    self.logger.info(f"skipped pre-existing tokenizer {model['name']} at {filepath}")
+                    self.logger.info(f"skipped pre-existing tokenizer {model['repo']} in {filepath}")
                     continue
                 self.resolve_tokenizer_model(filename, filepath, model)