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Browse files- README.md +36 -187
- config.json +2 -2
- mergekit_config.yml +16 -0
- model-00001-of-00002.safetensors +3 -0
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README.md
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---
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library_name: transformers
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tags:
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# Model Card for Model ID
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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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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### Model Sources [optional]
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- **Repository:** [More Information Needed]
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- **Paper [optional]:** [More Information Needed]
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- **Demo [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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### Direct Use
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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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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[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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[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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#### Speeds, Sizes, Times [optional]
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[More Information Needed]
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## Evaluation
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### Testing Data, Factors & Metrics
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#### Testing Data
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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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### Results
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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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#### Hardware
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#### Software
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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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base_model:
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- google/gemma-2-2b-jpn-it
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- zake7749/gemma-2-2b-it-chinese-kyara-dpo
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# merged_model
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the SLERP merge method.
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### Models Merged
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The following models were included in the merge:
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* [google/gemma-2-2b-jpn-it](https://huggingface.co/google/gemma-2-2b-jpn-it)
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* [zake7749/gemma-2-2b-it-chinese-kyara-dpo](https://huggingface.co/zake7749/gemma-2-2b-it-chinese-kyara-dpo)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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slices:
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- sources:
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- model: zake7749/gemma-2-2b-it-chinese-kyara-dpo
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layer_range: [0, 26]
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- model: google/gemma-2-2b-jpn-it
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layer_range: [0, 26]
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merge_method: slerp
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base_model: zake7749/gemma-2-2b-it-chinese-kyara-dpo
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.25, 0.5, 0.75, 1]
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- filter: mlp
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value: [1, 0.75, 0.5, 0.25, 0]
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- value: 0.5
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dtype: bfloat16
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```
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config.json
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{
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"_name_or_path": "
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"architectures": [
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"Gemma2ForCausalLM"
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"torch_dtype": "
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"transformers_version": "4.46.1",
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"use_cache": true,
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"vocab_size": 256000
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{
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"_name_or_path": "zake7749/gemma-2-2b-it-chinese-kyara-dpo",
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"architectures": [
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"Gemma2ForCausalLM"
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],
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.46.1",
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"use_cache": true,
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"vocab_size": 256000
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mergekit_config.yml
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slices:
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- sources:
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- model: zake7749/gemma-2-2b-it-chinese-kyara-dpo
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layer_range: [0, 26]
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- model: google/gemma-2-2b-jpn-it
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layer_range: [0, 26]
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merge_method: slerp
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base_model: zake7749/gemma-2-2b-it-chinese-kyara-dpo
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.25, 0.5, 0.75, 1]
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- filter: mlp
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value: [1, 0.75, 0.5, 0.25, 0]
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- value: 0.5
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dtype: bfloat16
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model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b9685e5c248c471cdfc1b6765c1916fbc92731aaede8ef772767c3e2952fc577
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size 4959718480
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model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:d7485874606fa8193a119901f3684fbaffc65d5661e102059804afd2d5200228
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size 268999016
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model.safetensors.index.json
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