初始化项目，由ModelHub XC社区提供模型
Model: migtissera/SynthIA-7B-v1.5 Source: Original Platform
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README.md
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---
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license: apache-2.0
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pipeline_tag: text-generation
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language:
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- en
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library_name: transformers
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---
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<br>
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<br>
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## Example Usage
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### Prompt format:
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```
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SYSTEM: Elaborate on the topic using a Tree of Thoughts and backtrack when necessary to construct a clear, cohesive Chain of Thought reasoning. Always answer without hesitation.
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USER: How is a rocket launched from the surface of the earth to Low Earth Orbit?
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ASSISTANT:
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```
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### Code example:
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```python
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import torch, json
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_path = "migtissera/SynthIA-7B-v1.5"
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output_file_path = "./SynthIA-7B-v1.5-conversations.jsonl"
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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torch_dtype=torch.float16,
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device_map="auto",
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load_in_8bit=False,
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trust_remote_code=True,
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)
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tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
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def generate_text(instruction):
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tokens = tokenizer.encode(instruction)
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tokens = torch.LongTensor(tokens).unsqueeze(0)
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tokens = tokens.to("cuda")
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instance = {
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"input_ids": tokens,
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"top_p": 1.0,
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"temperature": 0.75,
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"generate_len": 1024,
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"top_k": 50,
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}
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length = len(tokens[0])
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with torch.no_grad():
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rest = model.generate(
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input_ids=tokens,
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max_length=length + instance["generate_len"],
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use_cache=True,
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do_sample=True,
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top_p=instance["top_p"],
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temperature=instance["temperature"],
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top_k=instance["top_k"],
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num_return_sequences=1,
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)
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output = rest[0][length:]
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string = tokenizer.decode(output, skip_special_tokens=True)
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answer = string.split("USER:")[0].strip()
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return f"{answer}"
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conversation = f"SYSTEM: Elaborate on the topic using a Tree of Thoughts and backtrack when necessary to construct a clear, cohesive Chain of Thought reasoning. Always answer without hesitation."
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while True:
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user_input = input("You: ")
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llm_prompt = f"{conversation} \nUSER: {user_input} \nASSISTANT: "
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answer = generate_text(llm_prompt)
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print(answer)
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conversation = f"{llm_prompt}{answer}"
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json_data = {"prompt": user_input, "answer": answer}
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## Save your conversation
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with open(output_file_path, "a") as output_file:
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output_file.write(json.dumps(json_data) + "\n")
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_migtissera__SynthIA-7B-v1.5)
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| Metric | Value |
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|-----------------------|---------------------------|
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| Avg. | 54.8 |
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| ARC (25-shot) | 62.71 |
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| HellaSwag (10-shot) | 83.37 |
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| MMLU (5-shot) | 63.48 |
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| TruthfulQA (0-shot) | 51.32 |
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| Winogrande (5-shot) | 79.24 |
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| GSM8K (5-shot) | 17.44 |
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| DROP (3-shot) | 26.01 |
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config.json
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{
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"_name_or_path": "/home/ubuntu/llm/Mistral-7B-v0.1",
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"architectures": [
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"MistralForCausalLM"
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],
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"bos_token_id": 1,
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"eos_token_id": 2,
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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": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.34.0.dev0",
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"use_cache": true,
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"vocab_size": 32000
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}
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configuration.json
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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"model.layers.8.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.8.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.8.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.8.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.input_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.mlp.down_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.mlp.gate_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.mlp.up_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.post_attention_layernorm.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.self_attn.k_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.self_attn.o_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.self_attn.q_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.layers.9.self_attn.v_proj.weight": "pytorch_model-00001-of-00002.bin",
|
||||
"model.norm.weight": "pytorch_model-00002-of-00002.bin"
|
||||
}
|
||||
}
|
||||
5
special_tokens_map.json
Normal file
5
special_tokens_map.json
Normal file
@@ -0,0 +1,5 @@
|
||||
{
|
||||
"bos_token": "<s>",
|
||||
"eos_token": "</s>",
|
||||
"unk_token": "<unk>"
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
BIN
tokenizer.model
(Stored with Git LFS)
Normal file
Binary file not shown.
40
tokenizer_config.json
Normal file
40
tokenizer_config.json
Normal file
@@ -0,0 +1,40 @@
|
||||
{
|
||||
"added_tokens_decoder": {
|
||||
"0": {
|
||||
"content": "<unk>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"1": {
|
||||
"content": "<s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"2": {
|
||||
"content": "</s>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": [],
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"legacy": true,
|
||||
"model_max_length": 1000000000000000019884624838656,
|
||||
"pad_token": null,
|
||||
"sp_model_kwargs": {},
|
||||
"spaces_between_special_tokens": false,
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": true
|
||||
}
|
||||
Reference in New Issue
Block a user