Trained with Unsloth
Browse files- README.md +1 -52
- config.json +30 -0
- generation_config.json +6 -0
- pytorch_model-00001-of-00005.bin +3 -0
- pytorch_model-00002-of-00005.bin +3 -0
- pytorch_model-00003-of-00005.bin +3 -0
- pytorch_model-00004-of-00005.bin +3 -0
- pytorch_model-00005-of-00005.bin +3 -0
- pytorch_model.bin.index.json +442 -0
README.md
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license: apache-2.0
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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-llama/Meta-Llama-3-8B
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- beratcmn/Llama-3-11.5B
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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- trl
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base_model: beratcmn/Llama-3-11.5B
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---
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# Llama-3-11.5B
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This model is a Proof of Concept. First 2 Llama-3-8B models has been merged using `Mergekit` and pre-training continued using `QLora` and `Unsloth` for 1000 samples from `roneneldan/TinyStories`.
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Loss still decreases each epoch so I believe this is a successful experiment where there is a lot of room to experiment.
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Llama-3-11.5B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
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* [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)
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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-llama/Meta-Llama-3-8B
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layer_range: [0, 24]
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- sources:
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- model: meta-llama/Meta-Llama-3-8B
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layer_range: [8, 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 = "beratcmn/Llama-3-11.5B"
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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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# Uploaded model
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- llama
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- trl
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- sft
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base_model: beratcmn/Llama-3-11.5B
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---
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# Uploaded model
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config.json
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{
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"_name_or_path": "beratcmn/Llama-3-11.5B",
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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": 128000,
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"eos_token_id": 128001,
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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": 8192,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 48,
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"num_key_value_heads": 8,
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"pad_token_id": 128001,
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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": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.40.0",
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"unsloth_version": "2024.4",
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"use_cache": true,
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"vocab_size": 128256
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}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 128000,
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"eos_token_id": 128001,
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"transformers_version": "4.40.0"
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}
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pytorch_model-00001-of-00005.bin
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oid sha256:eabdf98b46ed2e246a5d84875545ad7b88ec9ddd6ed3e60c9a1a1ebf08cf0f70
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size 4976718466
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pytorch_model-00002-of-00005.bin
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size 4999827206
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pytorch_model-00003-of-00005.bin
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pytorch_model-00004-of-00005.bin
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version https://git-lfs.github.com/spec/v1
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pytorch_model-00005-of-00005.bin
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pytorch_model.bin.index.json
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