Upload

config.json

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+{
+  "_name_or_path": "./models/LMCocktail-10.7B-v1",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

export_log.txt

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+[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file tokenizer.model
+[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file added_tokens.json
+[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file special_tokens_map.json
+[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file tokenizer_config.json
+[INFO|tokenization_utils_base.py:2024] 2024-01-18 19:25:40,385 >> loading file tokenizer.json
+[INFO|configuration_utils.py:737] 2024-01-18 19:25:40,429 >> loading configuration file ./models/LMCocktail-10.7B-v1/config.json
+[INFO|configuration_utils.py:802] 2024-01-18 19:25:40,430 >> Model config LlamaConfig {
+  "_name_or_path": "./models/LMCocktail-10.7B-v1",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 8,
+  "pad_token_id": 2,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}
+
+[INFO|modeling_utils.py:3341] 2024-01-18 19:25:40,446 >> loading weights file ./models/LMCocktail-10.7B-v1/model.safetensors.index.json
+[INFO|modeling_utils.py:1341] 2024-01-18 19:25:40,447 >> Instantiating LlamaForCausalLM model under default dtype torch.float16.
+[INFO|configuration_utils.py:826] 2024-01-18 19:25:40,447 >> Generate config GenerationConfig {
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 2
+}
+
+
+[INFO|modeling_utils.py:4185] 2024-01-18 19:25:41,404 >> All model checkpoint weights were used when initializing LlamaForCausalLM.
+
+[INFO|modeling_utils.py:4193] 2024-01-18 19:25:41,404 >> All the weights of LlamaForCausalLM were initialized from the model checkpoint at ./models/LMCocktail-10.7B-v1.
+If your task is similar to the task the model of the checkpoint was trained on, you can already use LlamaForCausalLM for predictions without further training.
+[INFO|configuration_utils.py:779] 2024-01-18 19:25:41,407 >> loading configuration file ./models/LMCocktail-10.7B-v1/generation_config.json
+[INFO|configuration_utils.py:826] 2024-01-18 19:25:41,408 >> Generate config GenerationConfig {
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 2,
+  "use_cache": false
+}
+
+01/18/2024 19:25:41 - INFO - llmtuner.model.adapter - Fine-tuning method: LoRA
+01/18/2024 19:25:43 - INFO - llmtuner.model.adapter - Merged 1 adapter(s).
+01/18/2024 19:25:43 - INFO - llmtuner.model.adapter - Loaded adapter(s): ./models/sft/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1-lora
+01/18/2024 19:25:43 - INFO - llmtuner.model.loader - trainable params: 0 || all params: 10731524096 || trainable%: 0.0000
+01/18/2024 19:25:43 - INFO - llmtuner.model.loader - This IS expected that the trainable params is 0 if you are using model for inference only.
+[INFO|configuration_utils.py:483] 2024-01-18 19:25:43,941 >> Configuration saved in ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/config.json
+[INFO|configuration_utils.py:594] 2024-01-18 19:25:43,941 >> Configuration saved in ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/generation_config.json
+[INFO|modeling_utils.py:2390] 2024-01-18 19:26:02,405 >> The model is bigger than the maximum size per checkpoint (5GB) and is going to be split in 5 checkpoint shards. You can find where each parameters has been saved in the index located at ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/model.safetensors.index.json.
+[INFO|tokenization_utils_base.py:2432] 2024-01-18 19:26:02,406 >> tokenizer config file saved in ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2441] 2024-01-18 19:26:02,406 >> Special tokens file saved in ./models/export/LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1/special_tokens_map.json

generation_config.json

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+  "pad_token_id": 2,
+  "transformers_version": "4.36.2",
+  "use_cache": false
+}

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