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library_name: transformers
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license: apache-2.0
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---
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<!-- Provide a quick summary of what the model is/does. -->
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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## Uses
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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###
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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[More Information Needed]
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### Results
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[More Information Needed]
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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[More Information Needed]
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## Glossary [optional]
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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---
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library_name: transformers
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license: apache-2.0
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pipeline_tag: text-generation
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datasets:
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- maywell/ko_Ultrafeedback_binarized
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base model:
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- yanolja/EEVE-Korean-Instruct-10.8B-v1.0
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---
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/65f22e4076fedc4fd11e978f/MoTedec_ZL8GM2MmGyAPs.png)
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# T3Q-LLM-MG-v1.0
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## This model is a version of T3Q-LLM/T3Q-LLM-solar10.8-sft-v1.0 that has been fine-tuned with DPO.
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## Model Developers Chihoon Lee(chihoonlee10), T3Q
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### Python code
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
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MODEL_DIR = "chihoonlee10/T3Q-LLM-MG-v1.0"
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model = AutoModelForCausalLM.from_pretrained(MODEL_DIR, torch_dtype=torch.float16).to("cuda")
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tokenizer = AutoTokenizer.from_pretrained(MODEL_DIR)
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streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
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s = "한국의 수도는 어디?"
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conversation = [{'role': 'user', 'content': s}]
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inputs = tokenizer.apply_chat_template(
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conversation,
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tokenize=True,
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add_generation_prompt=True,
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return_tensors='pt').to("cuda")
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_ = model.generate(inputs, streamer=streamer, max_new_tokens=1024)
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```
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hf (pretrained=chihoonlee10/T3Q-LLM-MG-v1.0), limit: None, provide_description: False, num_fewshot: 0, batch_size: None
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| Task |Version| Metric |Value | |Stderr|
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|----------------|------:|--------|-----:|---|-----:|
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|kobest_boolq | 0|acc |0.9523|± |0.0057|
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| | |macro_f1|0.9523|± |0.0057|
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|kobest_copa | 0|acc |0.7740|± |0.0132|
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| | |macro_f1|0.7737|± |0.0133|
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|kobest_hellaswag| 0|acc |0.4980|± |0.0224|
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| | |acc_norm|0.5920|± |0.0220|
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| | |macro_f1|0.4950|± |0.0223|
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|kobest_sentineg | 0|acc |0.7254|± |0.0224|
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| | |macro_f1|0.7106|± |0.0234|
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### T3Q-LLM/T3Q-LLM-sft1.0-dpo1.0
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| Task |Version| Metric |Value | |Stderr|
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|----------------|------:|--------|-----:|---|-----:|
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|kobest_boolq | 0|acc |0.9387|± |0.0064|
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| | |macro_f1|0.9387|± |0.0064|
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|kobest_copa | 0|acc |0.7590|± |0.0135|
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| | |macro_f1|0.7585|± |0.0135|
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|kobest_hellaswag| 0|acc |0.5080|± |0.0224|
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| | |acc_norm|0.5580|± |0.0222|
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| | |macro_f1|0.5049|± |0.0224|
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|kobest_sentineg | 0|acc |0.8489|± |0.0180|
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| | |macro_f1|0.8483|± |0.0180|
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