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README.md
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---
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license: apache-2.0
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datasets:
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- WizardLM/WizardLM_evol_instruct_V2_196k
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- leemeng/ShareGPT90K_ja_1392
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- nlp
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- llm
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---
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# AmberChat
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We present AmberChat, an instruction following model finetuned from [LLM360/Amber](https://huggingface.co/LLM360/Amber).
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## Model Description
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- **Model type:** Language model with the same architecture as LLaMA-7B
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- **Language(s) (NLP):** English
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- **License:** Apache 2.0
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- **Original Checkpoints:** [Aws bucket with AmberChat checkpoint with all available optimizer states](https://aws.amazon.com/)
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- **Resources for more information:**
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- [Research paper](https://arxiv.org/)
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- [GitHub Repo](https://github.com/LLM360)
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- [Amber pretraining data](https://huggingface.co/)
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# Loading Amber
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```python
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from transformers import LlamaTokenizer, LlamaForCausalLM
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tokenizer = LlamaTokenizer.from_pretrained("LLM360/AmberChat")
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model = LlamaForCausalLM.from_pretrained("LLM360/AmberChat")
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input_text = "translate English to German: How old are you?"
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input_ids = tokenizer(input_text, return_tensors="pt").input_ids
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outputs = model.generate(input_ids)
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print(tokenizer.decode(outputs[0]))
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```
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# AmberChat Finetuning Details
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## DataMix
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| Subset | Number of rows |
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| ----------- | ----------- |
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| WizardLM/WizardLM_evol_instruct_V2_196k | 143k |
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| Sharegpt-90k | 90k |
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| Total | 233k |
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## Hyperparameters
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| Hyperparameter | Value |
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| ----------- | ----------- |
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| Total Parameters | 6.7B |
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| Hidden Size | 4096 |
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| Intermediate Size (MLPs) | 11008 |
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| Number of Attention Heads | 32 |
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| Number of Hidden Lyaers | 32 |
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| RMSNorm ɛ | 1e^-6 |
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| Max Seq Length | 2048 |
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| Vocab Size | 32000 |
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# Evaluation
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| Model | MT-Bench |
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|------------------------------------------------------|------------------------------------------------------------|
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| LLM360/Amber 359 | 2.48750 |
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| **LLM360/AmberChat** | **5.428125** |
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# Citation
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**BibTeX:**
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```bibtex
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@article{xxx,
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title={XXX},
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author={XXX},
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journal={XXX},
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year={2023}
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}
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```
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