[INIT] First Checkpoint (2024-03-09)

config.json

@@ -0,0 +1,26 @@
+{
+  "_name_or_path": "ZharfaTech/ZharfaOpen-0409",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 32000,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 8192,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.38.2",
+  "use_cache": true,
+  "vocab_size": 32002
+}

eval.py

@@ -0,0 +1,46 @@
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
+
+from peft import LoraConfig, PeftModel, prepare_model_for_kbit_training, get_peft_model
+
+model_id = "/share/models/open-zharfa"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, add_eos_token=True)
+
+base_model = AutoModelForCausalLM.from_pretrained(
+            model_id,
+            low_cpu_mem_usage=True,
+            return_dict=True,
+            torch_dtype=torch.float16,
+            device_map="auto",
+        )
+
+base_model.generation_config.do_sample = True 
+
+
+#tokenizer.pad_token = tokenizer.eos_token
+tokenizer.pad_token = tokenizer.unk_token
+tokenizer.padding_side = "right"
+
+def get_completion_merged(query: str, model, tokenizer) -> str:
+    device = "cuda:0"
+
+    prompt_template = """
+
+          GPT4 Correct User: {query}<|end_of_turn|>GPT4 Correct Assistant:
+
+    """
+    prompt = prompt_template.format(query=query)
+
+    encodeds = tokenizer(prompt, return_tensors="pt", add_special_tokens=True)
+
+    model_inputs = encodeds.to(device)
+
+    generated_ids = model.generate(**model_inputs, max_new_tokens=1000, do_sample=True, temperature=0.5, pad_token_id=tokenizer.unk_token_id)    #pad_token_id=tokenizer.eos_token_id)
+    decoded = tokenizer.batch_decode(generated_ids)
+    return (decoded[0])
+
+while True:
+    q = input('q : ')
+    result = get_completion_merged(query=q, model=base_model, tokenizer=tokenizer)
+    print(result)

generation_config.json

@@ -0,0 +1,10 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 32000,
+  "max_length": 8192,
+  "pad_token_id": 0,
+  "temperature": 0.5,
+  "transformers_version": "4.38.2"
+}

model-00001-of-00003.safetensors

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special_tokens_map.json

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+{
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+    "<|end_of_turn|>",
+    "<|pad_0|>"
+  ],
+  "bos_token": {
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+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+      "special": true
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+  "legacy": true,
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+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": true
+}