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Model: minlik/chinese-alpaca-13b-merged Source: Original Platform
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README.md
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README.md
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---
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title: chinese-alpaca-13b-merged
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emoji: 📚
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colorFrom: gray
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colorTo: red
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sdk: gradio
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sdk_version: 3.23.0
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app_file: app.py
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pinned: false
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---
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加入中文词表并继续预训练中文Embedding,并在此基础上继续使用指令数据集finetuning,得到的中文LLaMA模型。
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详情可参考:https://github.com/ymcui/Chinese-LLaMA-Alpaca
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### 使用方法参考
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1. 安装模块包
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```bash
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pip install sentencepiece
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pip install transformers>=4.28.0
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```
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2. 生成文本
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```python
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import torch
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import transformers
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from transformers import LlamaTokenizer, LlamaForCausalLM
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def generate_prompt(text):
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return f"""Below is an instruction that describes a task. Write a response that appropriately completes the request.
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### Instruction:
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{text}
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### Response:"""
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tokenizer = LlamaTokenizer.from_pretrained('minlik/chinese-alpaca-13b-merged')
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model = LlamaForCausalLM.from_pretrained('minlik/chinese-alpaca-13b-merged').half().to('cuda')
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model.eval()
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text = '第一个登上月球的人是谁?'
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prompt = generate_prompt(text)
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input_ids = tokenizer.encode(prompt, return_tensors='pt').to('cuda')
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with torch.no_grad():
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output_ids = model.generate(
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input_ids=input_ids,
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max_new_tokens=128,
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temperature=1,
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top_k=40,
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top_p=0.9,
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repetition_penalty=1.15
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).cuda()
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output = tokenizer.decode(output_ids[0], skip_special_tokens=True)
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print(output.replace(prompt, '').strip())
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```
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config.json
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config.json
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{
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"_name_or_path": "decapoda-research/llama-13b-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": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 13824,
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"max_position_embeddings": 2048,
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"max_sequence_length": 2048,
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"model_type": "llama",
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"num_attention_heads": 40,
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"num_hidden_layers": 40,
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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": 49954
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}
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}
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"model.layers.7.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.7.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.7.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.7.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.7.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.7.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.7.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.7.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.7.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.8.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.input_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.mlp.down_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.self_attn.rotary_emb.inv_freq": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00003.bin",
|
||||||
|
"model.norm.weight": "pytorch_model-00003-of-00003.bin"
|
||||||
|
}
|
||||||
|
}
|
||||||
6
special_tokens_map.json
Normal file
6
special_tokens_map.json
Normal file
@@ -0,0 +1,6 @@
|
|||||||
|
{
|
||||||
|
"bos_token": "<s>",
|
||||||
|
"eos_token": "</s>",
|
||||||
|
"pad_token": "[PAD]",
|
||||||
|
"unk_token": "<unk>"
|
||||||
|
}
|
||||||
3
tokenizer.model
Normal file
3
tokenizer.model
Normal file
@@ -0,0 +1,3 @@
|
|||||||
|
version https://git-lfs.github.com/spec/v1
|
||||||
|
oid sha256:2d967e855b1213a439df6c8ce2791f869c84b4f3b6cfacf22b86440b8192a2f8
|
||||||
|
size 757972
|
||||||
33
tokenizer_config.json
Normal file
33
tokenizer_config.json
Normal file
@@ -0,0 +1,33 @@
|
|||||||
|
{
|
||||||
|
"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": 1000000000000000019884624838656,
|
||||||
|
"pad_token": null,
|
||||||
|
"sp_model_kwargs": {},
|
||||||
|
"tokenizer_class": "LlamaTokenizer",
|
||||||
|
"unk_token": {
|
||||||
|
"__type": "AddedToken",
|
||||||
|
"content": "<unk>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": true,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false
|
||||||
|
}
|
||||||
|
}
|
||||||
Reference in New Issue
Block a user