Create hello_world_model.safetensors

hello_world_model.safetensors

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+import torch
+from transformers import PreTrainedModel, PreTrainedTokenizerFast, PretrainedConfig, CausalLMOutput
+
+# Define the model configuration
+class HelloWorldConfig(PretrainedConfig):
+    model_type = "hello-world"
+    vocab_size = 2
+    bos_token_id = 0
+    eos_token_id = 1
+
+# Define the model
+class HelloWorldModel(PreTrainedModel):
+    config_class = HelloWorldConfig
+
+    def __init__(self, config):
+        super().__init__(config)
+
+    def forward(self, input_ids=None, **kwargs):
+        batch_size = input_ids.shape[0]
+        sequence_length = input_ids.shape[1]
+
+        # Generate logits for the "Hello, world!" token
+        hello_world_token_id = self.config.vocab_size - 1
+        logits = torch.full((batch_size, sequence_length, self.config.vocab_size), float('-inf'))
+        logits[:, :, hello_world_token_id] = 0
+
+        return CausalLMOutput(logits=logits)
+
+# Define and save the tokenizer
+tokenizer = PreTrainedTokenizerFast(tokenizer_file="tokenizer.json")
+tokenizer.add_tokens(["Hello, world!"])
+
+tokenizer_config = {
+    "do_lower_case": False,
+    "model_max_length": 512,
+    "padding_side": "right",
+    "special_tokens_map_file": None,
+    "tokenizer_file": "tokenizer.json",
+    "unk_token": "<unk>",
+    "bos_token": "<s>",
+    "eos_token": "</s>",
+    "vocab_size": 2,
+}
+
+with open("tokenizer.json", "w") as f:
+    json.dump(tokenizer_config, f)
+
+# Initialize model
+config = HelloWorldConfig()
+model = HelloWorldModel(config)
+
+# Save model using safetensors format
+from safetensors.torch import save_file
+save_file(model.state_dict(), "hello_world_model.safetensors")