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Duplicate from arvindanand/validateAI
Browse files- .gitattributes +35 -0
- README.md +68 -0
- config.json +31 -0
- generation_config.json +6 -0
- model-00001-of-00007.safetensors +3 -0
- model-00002-of-00007.safetensors +3 -0
- model-00003-of-00007.safetensors +3 -0
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- model-00006-of-00007.safetensors +3 -0
- model-00007-of-00007.safetensors +3 -0
- model.safetensors.index.json +1 -0
- tokenizer.json +0 -0
- tokenizer_config.json +34 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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tags:
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- merge
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- mergekit
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- lazymergekit
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- WizardLM/WizardCoder-33B-V1.1
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- codefuse-ai/CodeFuse-DeepSeek-33B
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- deepseek-ai/deepseek-coder-33b-instruct
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base_model:
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- deepseek-ai/deepseek-coder-33b-instruct
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license: apache-2.0
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---
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# ValidateAI
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ValidateAI is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [deepseek-ai/deepseek-coder-33b-instruct](https://huggingface.co/deepseek-ai/deepseek-coder-33b-instruct)
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* [WizardLM/WizardCoder-33B-V1.1](https://huggingface.co/WizardLM/WizardCoder-33B-V1.1)
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* [codefuse-ai/CodeFuse-DeepSeek-33B](https://huggingface.co/codefuse-ai/CodeFuse-DeepSeek-33B)
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*
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## 🧩 Configuration
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```yaml
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models:
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- model: codefuse-ai_CodeFuse-DeepSeek-33B
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parameters:
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weight: 1
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- model: deepseek-ai_deepseek-coder-33b-instruct
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parameters:
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weight: 1
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- model: WizardLM_WizardCoder-33B-V1.1
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parameters:
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weight: 1
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merge_method: task_arithmetic
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base_model: deepseek-ai_deepseek-coder-33b-base
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parameters:
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normalize: true
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int8_mask: true
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dtype: float16
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```
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "arvind22/ValidateAI"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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config.json
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{
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"_name_or_path": "Everyone-Coder-33b-v2-Base",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 32013,
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"eos_token_id": 32014,
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"hidden_act": "silu",
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"hidden_size": 7168,
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"initializer_range": 0.02,
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"intermediate_size": 19200,
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"max_position_embeddings": 16384,
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"model_type": "llama",
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"num_attention_heads": 56,
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"num_hidden_layers": 62,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-06,
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"rope_scaling": {
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"factor": 4.0,
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"type": "linear"
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},
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"rope_theta": 100000,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.36.2",
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"use_cache": true,
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"vocab_size": 32256
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}
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generation_config.json
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tokenizer_config.json
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{
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"add_bos_token": true,
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"add_eos_token": false,
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"bos_token": {
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"__type": "AddedToken",
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"content": "<|begin▁of▁sentence|>",
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"eos_token": {
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"__type": "AddedToken",
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"content": "<|end▁of▁sentence|>",
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"single_word": false
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},
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"pad_token": {
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"__type": "AddedToken",
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"content": "<|end▁of▁sentence|>",
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},
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"sp_model_kwargs": {},
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"unk_token": null,
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"tokenizer_class": "LlamaTokenizerFast"
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}
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