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README.md
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@@ -28,6 +28,8 @@ We will extend the model to train on larger data sets and different base models
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We release both pre-trained base models and instruction tuned variants with 270M and 1.1B parameters.
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Along with the model, datasets used to train the base and instruction-tuned models are also released.
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List of released models:
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* [Taiwan-ELM-270M](https://huggingface.co/liswei/Taiwan-ELM-270M)
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* [Taiwan-ELM-1_1B](https://huggingface.co/liswei/Taiwan-ELM-1_1B)
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List of released datasets:
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* [liswei/Taiwan-Text-Excellence-2B](https://huggingface.co/datasets/liswei/Taiwan-Text-Excellence-2B)
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* [liswei/PromptPair-TW](https://huggingface.co/datasets/liswei/PromptPair-TW)
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## Usage Examples
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```jinja2
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<s>[INST] <<SYS>>
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{{ system_prompt }}
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{{ user_message }} [/INST]
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```
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The model could be load via `AutoModelForCausalLM` with `trust_remote_code=True`:
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```python
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```
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We also support additional generation methods and speculative generation, please find reference at [OpenELM#usage](https://huggingface.co/apple/OpenELM#usage).
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We release both pre-trained base models and instruction tuned variants with 270M and 1.1B parameters.
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Along with the model, datasets used to train the base and instruction-tuned models are also released.
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In an effort to improve transparency, training checkpoints (including rng/optimizer state) and training logs are also released in the model page.
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List of released models:
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* [Taiwan-ELM-270M](https://huggingface.co/liswei/Taiwan-ELM-270M)
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* [Taiwan-ELM-1_1B](https://huggingface.co/liswei/Taiwan-ELM-1_1B)
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List of released datasets:
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* [liswei/Taiwan-Text-Excellence-2B](https://huggingface.co/datasets/liswei/Taiwan-Text-Excellence-2B)
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* [liswei/PromptPair-TW](https://huggingface.co/datasets/liswei/PromptPair-TW)
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* [liswei/wikinews-zhtw-dedup](https://huggingface.co/datasets/liswei/wikinews-zhtw-dedup)
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* [liswei/wikipedia-zhtw-dedup](https://huggingface.co/datasets/liswei/wikipedia-zhtw-dedup)
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* [liswei/coct-en-zhtw-dedup](liswei/coct-en-zhtw-dedup)
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Some of the datasets are not used for training Taiwan ELM but also released:
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* [liswei/common-crawl-zhtw](liswei/common-crawl-zhtw)
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* [liswei/c4-zhtw](liswei/c4-zhtw)
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* [liswei/rm-static-zhTW](liswei/rm-static-zhTW)
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## Usage Examples
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For instruction-tuned modesl, we adapt the [LLaMA2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) template:
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```jinja2
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<s>[INST] <<SYS>>
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{{ system_prompt }}
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{{ user_message }} [/INST]
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```
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The model could be load via `AutoModelForCausalLM` and `text-generation-inference` with `trust_remote_code=True`:
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```python
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taiwan_elm_270m = AutoModelForCausalLM.from_pretrained("liswei/Taiwan-ELM-270M", trust_remote_code=True)
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```
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We also support additional generation methods and speculative generation, please find reference at [OpenELM#usage](https://huggingface.co/apple/OpenELM#usage).
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