test translation

novel-translation/08_eval-lf-py3.11.ipynb

@@ -1360,7 +1360,7 @@
     "    print(f\"Epoch {i}\")\n",
     "    adapter_path = f\"llama-factory/saves/qwen2-0.5b/lora/sft/checkpoint-{560 * i}\"\n",
     "    os.environ[\"ADAPTER_NAME_OR_PATH\"] = adapter_path\n",
-    "    !python llm_toolkit/eval_mac.py "
+    "    !python llm_toolkit/eval.py "
    ]
   },
   {
@@ -2517,7 +2517,44 @@
     "    print(f\"Epoch {i}\")\n",
     "    adapter_path = f\"llama-factory/saves/qwen2-1.5b/lora/sft/checkpoint-{560 * i}\"\n",
     "    os.environ[\"ADAPTER_NAME_OR_PATH\"] = adapter_path\n",
-    "    !python llm_toolkit/eval_mac.py "
+    "    !python llm_toolkit/eval.py "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%%time\n",
+    "\n",
+    "os.environ[\"MODEL_NAME\"] = \"Qwen/Qwen2-7B-Instruct\" \n",
+    "for i in range(1, num_train_epochs + 1):\n",
+    "    print(f\"Epoch {i}\")\n",
+    "    adapter_path = f\"llama-factory/saves/qwen2-7b/lora/sft/checkpoint-{560 * i}\"\n",
+    "    os.environ[\"ADAPTER_NAME_OR_PATH\"] = adapter_path\n",
+    "    !python llm_toolkit/eval.py "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain_openai import ChatOpenAI\n",
+    "\n",
+    "llm = ChatOpenAI(\n",
+    "    model=\"gpt-4o\",\n",
+    "    temperature=0,\n",
+    "    max_tokens=None,\n",
+    "    timeout=None,\n",
+    "    max_retries=2,\n",
+    "    # api_key=\"...\",  # if you prefer to pass api key in directly instaed of using env vars\n",
+    "    base_url=\"http://localhost:8000/v1\",\n",
+    "    # organization=\"...\",\n",
+    "    # other params...\n",
+    ")"
    ]
   },
   {
@@ -2544,29 +2581,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "'According to his logic, this red, stiff, one-foot-long thing on my body was the embodiment of sin.'"
+       "'The body was found on the morning beach'"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 28,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "translate_via_llm(\n",
-    "    \"按他的逻辑，我身上这个通红通红，直不愣登，长约一尺的东西就是罪恶的化身。\"\n",
-    ")"
+    "translate_via_llm(\"死者凌晨去的沙滩\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2575,23 +2610,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'按他的逻辑，我身上这个通红通红，直不愣登，长约一尺的东西就是罪恶的化身。': 'According to his logic, this red, stiff, one-foot-long thing on my body was the embodiment of sin.'}"
+       "{'死者凌晨去的沙滩': 'The body was found on the morning beach'}"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "translate(\n",
-    "    \"按他的逻辑，我身上这个通红通红，直不愣登，长约一尺的东西就是罪恶的化身。\",\n",
+    "    \"死者凌晨去的沙滩\",\n",
     "    cache_dict=cache_dict,\n",
     ")\n",
     "cache_dict"