Upload XmodForSequenceClassification
Browse files- README.md +201 -0
- config.json +123 -0
- model.safetensors +3 -0
README.md
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---
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library_name: transformers
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tags: []
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---
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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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<!-- Provide the basic links for the model. -->
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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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<!-- 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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config.json
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{
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"_name_or_path": "kangXn/enhi-tp",
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"adapter_layer_norm": false,
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"adapter_reduction_factor": 2,
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"adapter_reuse_layer_norm": true,
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"architectures": [
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"XmodForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"default_language": "hi_IN",
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"eos_token_id": 2,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "LABEL_0"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"LABEL_0": 0
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},
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"languages": [
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"en_XX",
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"id_ID",
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"vi_VN",
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"ru_RU",
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"fa_IR",
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"sv_SE",
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"ja_XX",
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"fr_XX",
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"de_DE",
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"ro_RO",
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"ko_KR",
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"hu_HU",
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"es_XX",
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"fi_FI",
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"uk_UA",
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"da_DK",
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"pt_XX",
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"no_XX",
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"th_TH",
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"pl_PL",
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"bg_BG",
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"nl_XX",
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"zh_CN",
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"he_IL",
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"el_GR",
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"it_IT",
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"sk_SK",
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"hr_HR",
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"tr_TR",
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"ar_AR",
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"cs_CZ",
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"lt_LT",
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"hi_IN",
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"zh_TW",
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"ca_ES",
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"ms_MY",
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"sl_SI",
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"lv_LV",
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"ta_IN",
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"bn_IN",
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"et_EE",
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"az_AZ",
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"sq_AL",
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"sr_RS",
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"kk_KZ",
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"ka_GE",
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"tl_XX",
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"ur_PK",
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"is_IS",
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"hy_AM",
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"ml_IN",
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"mk_MK",
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"be_BY",
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"la_VA",
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"te_IN",
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"eu_ES",
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"gl_ES",
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"mn_MN",
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"kn_IN",
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"ne_NP",
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"sw_KE",
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"si_LK",
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"mr_IN",
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"af_ZA",
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"gu_IN",
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"cy_GB",
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"eo_EO",
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"km_KH",
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"ky_KG",
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"uz_UZ",
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"ps_AF",
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"pa_IN",
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"ga_IE",
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"ha_NG",
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"am_ET",
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"lo_LA",
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"ku_TR",
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"so_SO",
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"my_MM",
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"or_IN",
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"sa_IN"
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],
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"layer_norm_eps": 1e-05,
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"ln_before_adapter": true,
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"max_position_embeddings": 514,
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"model_type": "xmod",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"pre_norm": false,
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"problem_type": "regression",
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"torch_dtype": "float32",
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"transformers_version": "4.38.2",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3ad5d98cfca67028aa739e1662b3d971ce92c7c258c4bed6aa93994ee392f050
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size 3410454016
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