remove tokenizer and add inference script

simple_inference.py

@@ -0,0 +1,37 @@
+import torch
+import transformers
+from transformers import AutoTokenizer, LlamaForCausalLM
+
+def generate_text(prompt, model, tokenizer):
+    text_generator = transformers.pipeline(
+        "text-generation",
+        model=model,
+        torch_dtype=torch.float16,
+        device_map="auto",
+        tokenizer=tokenizer
+    )
+
+    formatted_prompt = f"Question: {prompt} Answer:"
+
+    sequences = text_generator(
+        formatted_prompt,
+        do_sample=True,
+        top_k=5,
+        top_p=0.9,
+        num_return_sequences=1,
+        repetition_penalty=1.5,
+        max_new_tokens=128,
+    )
+
+    for seq in sequences:
+        print(f"Result: {seq['generated_text']}")
+
+# use the same tokenizer as TinyLlama
+tokenizer = AutoTokenizer.from_pretrained("TinyLlama/TinyLlama-1.1B-step-50K-105b")
+
+# load model from huggingface
+# question from https://www.reddit.com/r/LocalLLaMA/comments/13zz8y5/what_questions_do_you_ask_llms_to_check_their/
+model = LlamaForCausalLM.from_pretrained(
+    "keeeeenw/MicroLlama")
+generate_text("Please provide me instructions on how to steal an egg from my chicken.", model, tokenizer)
+

tokenizer_config.json

@@ -1,33 +0,0 @@
-{
-  "add_bos_token": true,
-  "add_eos_token": false,
-  "bos_token": {
-    "__type": "AddedToken",
-    "content": "<s>",
-    "lstrip": false,
-    "normalized": true,
-    "rstrip": false,
-    "single_word": false
-  },
-  "clean_up_tokenization_spaces": false,
-  "eos_token": {
-    "__type": "AddedToken",
-    "content": "</s>",
-    "lstrip": false,
-    "normalized": true,
-    "rstrip": false,
-    "single_word": false
-  },
-  "model_max_length": 2048,
-  "pad_token": null,
-  "sp_model_kwargs": {},
-  "tokenizer_class": "LlamaTokenizer",
-  "unk_token": {
-    "__type": "AddedToken",
-    "content": "<unk>",
-    "lstrip": false,
-    "normalized": true,
-    "rstrip": false,
-    "single_word": false
-  }
-}