confettiwap
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Browse files- README.md +56 -0
- config.json +29 -0
- mergekit_config.yml +10 -0
- model-00001-of-00019.safetensors +3 -0
- model-00002-of-00019.safetensors +3 -0
- model-00003-of-00019.safetensors +3 -0
- model-00004-of-00019.safetensors +3 -0
- model-00005-of-00019.safetensors +3 -0
- model-00006-of-00019.safetensors +3 -0
- model-00007-of-00019.safetensors +3 -0
- model-00008-of-00019.safetensors +3 -0
- model-00009-of-00019.safetensors +3 -0
- model-00010-of-00019.safetensors +3 -0
- model-00011-of-00019.safetensors +3 -0
- model-00012-of-00019.safetensors +3 -0
- model-00013-of-00019.safetensors +3 -0
- model-00014-of-00019.safetensors +3 -0
- model-00015-of-00019.safetensors +3 -0
- model-00016-of-00019.safetensors +3 -0
- model-00017-of-00019.safetensors +3 -0
- model-00018-of-00019.safetensors +3 -0
- model-00019-of-00019.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +23 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +40 -0
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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- meta-math/MetaMath-Mistral-7B
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- EleutherAI/llemma_7b
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base_model:
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- meta-math/MetaMath-Mistral-7B
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- EleutherAI/llemma_7b
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---
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# MM-SL
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MM-SL is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
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* [EleutherAI/llemma_7b](https://huggingface.co/EleutherAI/llemma_7b)
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## 🧩 Configuration
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```yaml
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slices:
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- sources:
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- model: meta-math/MetaMath-Mistral-7B
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layer_range: [0, 32]
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- sources:
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- model: EleutherAI/llemma_7b
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layer_range: [24, 32]
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merge_method: passthrough
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dtype: bfloat16
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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 = "confettiwap/MM-SL"
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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": "EleutherAI/llemma_7b",
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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": 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": 11008,
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"max_position_embeddings": 4096,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 40,
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"num_key_value_heads": 32,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.40.2",
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"use_cache": true,
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"vocab_size": 32016
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}
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mergekit_config.yml
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slices:
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- sources:
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- model: meta-math/MetaMath-Mistral-7B
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layer_range: [0, 32]
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- sources:
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- model: EleutherAI/llemma_7b
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layer_range: [24, 32]
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merge_method: passthrough
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dtype: bfloat16
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model-00001-of-00019.safetensors
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special_tokens_map.json
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tokenizer.json
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tokenizer.model
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tokenizer_config.json
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