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add model weights

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  1. README.md +20 -0
  2. config.json +23 -0
  3. generation_config.json +7 -0
  4. pytorch_model-00001-of-00039.bin +3 -0
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README.md ADDED
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+ # Alpaca LoRa 7B
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+
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+ This repository contains a LLaMA-7B fine-tuned model on the [Standford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) cleaned version dataset.
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+
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+ I used [LLaMA-7B-hf](decapoda-research/llama-7b-hf) as a base model
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+
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+ # Usage
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+
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+ ## Using the model
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+
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+ ```python
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+ from transformers import LlamaTokenizer, LlamaForCausalLM,
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+
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+ tokenizer = LlamaTokenizer.from_pretrained("decapoda-research/alpaca-lora-7b")
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+ model = LlamaForCausalLM.from_pretrained(
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+ "chainyo/alpaca-lora-7b",
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+ load_in_8bit=True,
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+ torch_dtype=torch.float16,
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+ device_map="auto",
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+ )
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+ {
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+ "_name_or_path": "decapoda-research/llama-7b-hf",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "bos_token_id": 0,
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+ "eos_token_id": 1,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 11008,
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+ "max_sequence_length": 2048,
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+ "model_type": "llama",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "pad_token_id": -1,
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+ "rms_norm_eps": 1e-06,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float16",
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+ "transformers_version": "4.28.0.dev0",
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+ "use_cache": true,
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+ "vocab_size": 32000
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+ }
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+ "_from_model_config": true,
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+ "bos_token_id": 0,
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+ "eos_token_id": 1,
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+ "pad_token_id": 0,
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+ "transformers_version": "4.28.0.dev0"
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+ }
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