Upload DebertaV2ForSequenceClassification
Browse files- README.md +199 -0
- config.json +80 -0
- model-00001-of-00002.safetensors +3 -0
- model-00002-of-00002.safetensors +3 -0
- model.safetensors.index.json +789 -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": "/output_perm/models/RS_66_hv_eng_nw",
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"architectures": [
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"DebertaV2ForSequenceClassification"
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],
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"attention_head_size": 64,
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"attention_probs_dropout_prob": 0.1,
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"conv_act": "gelu",
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"conv_kernel_size": 3,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 1536,
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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3",
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"4": "LABEL_4",
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"5": "LABEL_5",
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"6": "LABEL_6",
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"7": "LABEL_7",
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"8": "LABEL_8",
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"9": "LABEL_9",
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"10": "LABEL_10",
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"11": "LABEL_11",
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"12": "LABEL_12",
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"13": "LABEL_13",
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"14": "LABEL_14",
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"15": "LABEL_15",
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"16": "LABEL_16",
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"17": "LABEL_17",
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"18": "LABEL_18"
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},
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"initializer_range": 0.02,
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"intermediate_size": 6144,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_10": 10,
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"LABEL_11": 11,
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"LABEL_12": 12,
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"LABEL_13": 13,
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"LABEL_14": 14,
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"LABEL_15": 15,
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"LABEL_16": 16,
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"LABEL_17": 17,
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"LABEL_18": 18,
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"LABEL_2": 2,
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"LABEL_3": 3,
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"LABEL_4": 4,
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"LABEL_5": 5,
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"LABEL_6": 6,
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"LABEL_7": 7,
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"LABEL_8": 8,
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"LABEL_9": 9
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},
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"layer_norm_eps": 1e-07,
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"max_position_embeddings": 512,
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"max_relative_positions": -1,
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"model_type": "deberta-v2",
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"norm_rel_ebd": "layer_norm",
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"num_attention_heads": 24,
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"num_hidden_layers": 48,
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"pad_token_id": 0,
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"pooler_dropout": 0,
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"pooler_hidden_act": "gelu",
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"pooler_hidden_size": 1536,
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"pos_att_type": [
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"p2c",
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"c2p"
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],
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"position_biased_input": false,
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"position_buckets": 256,
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"relative_attention": true,
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"share_att_key": true,
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"torch_dtype": "float32",
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"transformers_version": "4.39.3",
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"type_vocab_size": 0,
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"vocab_size": 128100
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}
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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 sha256:6f9d3751f400bc6fab7ea30801dfc7dd1acf578ece651845ec1156967e751a16
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size 4999085984
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model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:897ff04f9c0de12f1050f1abd692a4583242e377f878e169fac8d9075638b833
|
| 3 |
+
size 1268770940
|
model.safetensors.index.json
ADDED
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@@ -0,0 +1,789 @@
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|
| 1 |
+
{
|
| 2 |
+
"metadata": {
|
| 3 |
+
"total_size": 6267758668
|
| 4 |
+
},
|
| 5 |
+
"weight_map": {
|
| 6 |
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"classifier.bias": "model-00002-of-00002.safetensors",
|
| 7 |
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"classifier.weight": "model-00002-of-00002.safetensors",
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| 8 |
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"deberta.embeddings.LayerNorm.bias": "model-00001-of-00002.safetensors",
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| 9 |
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"deberta.embeddings.LayerNorm.weight": "model-00001-of-00002.safetensors",
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| 10 |
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"deberta.embeddings.word_embeddings.weight": "model-00001-of-00002.safetensors",
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| 11 |
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"deberta.encoder.LayerNorm.bias": "model-00002-of-00002.safetensors",
|
| 12 |
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"deberta.encoder.LayerNorm.weight": "model-00002-of-00002.safetensors",
|
| 13 |
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"deberta.encoder.conv.LayerNorm.bias": "model-00002-of-00002.safetensors",
|
| 14 |
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"deberta.encoder.conv.LayerNorm.weight": "model-00002-of-00002.safetensors",
|
| 15 |
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"deberta.encoder.conv.conv.bias": "model-00002-of-00002.safetensors",
|
| 16 |
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"deberta.encoder.conv.conv.weight": "model-00002-of-00002.safetensors",
|
| 17 |
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"deberta.encoder.layer.0.attention.output.LayerNorm.bias": "model-00001-of-00002.safetensors",
|
| 18 |
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"deberta.encoder.layer.0.attention.output.LayerNorm.weight": "model-00001-of-00002.safetensors",
|
| 19 |
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"deberta.encoder.layer.0.attention.output.dense.bias": "model-00001-of-00002.safetensors",
|
| 20 |
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"deberta.encoder.layer.0.attention.output.dense.weight": "model-00001-of-00002.safetensors",
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| 21 |
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"deberta.encoder.layer.0.attention.self.key_proj.bias": "model-00001-of-00002.safetensors",
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| 22 |
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"deberta.encoder.layer.0.attention.self.key_proj.weight": "model-00001-of-00002.safetensors",
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| 23 |
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"deberta.encoder.layer.0.attention.self.query_proj.bias": "model-00001-of-00002.safetensors",
|
| 24 |
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"deberta.encoder.layer.0.attention.self.query_proj.weight": "model-00001-of-00002.safetensors",
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