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  ---
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  base_model: meta-llama/Llama-3.2-1B
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  library_name: peft
 
 
 
 
 
 
 
 
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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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- - **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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- #### 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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- [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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- **APA:**
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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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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
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- ### Framework versions
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- - PEFT 0.13.2
 
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  ---
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  base_model: meta-llama/Llama-3.2-1B
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  library_name: peft
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+ license: apache-2.0
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+ datasets:
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+ - trumancai/revela_code_training_corpus
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+ language:
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+ - en
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+ tags:
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+ - retrieval
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+ - code
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  ---
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+ # Model Summary
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+ **Revela-code-3b** is a self-supervised code retriever built on the 3 B-parameter **LLaMA-3.2-3B** backbone.
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+ It was trained on 358 K batches of code-centric text (Stack Overflow, tutorials, API docs) using the Revela next-token-prediction + in-batch attention objective.
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+ Use it for code-search, question-answer navigation, or hybrid doc/code retrieval.
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+ - **Repository:** [TRUMANCFY/Revela](https://github.com/TRUMANCFY/Revela)
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+ - **Training Dataset:** [trumancai/revela_code_training_corpus](https://huggingface.co/datasets/trumancai/revela_code_training_corpus)
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+
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+ # Other Links
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+ | Binary | Description |
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+ |:-------|:------------|
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+ | [trumancai/Revela-code-3b](https://huggingface.co/trumancai/Revela-code-3b) | 3 B-parameter code-retriever. |
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+ | [trumancai/Revela-code-1b](https://huggingface.co/trumancai/Revela-code-1b) | 1 B-parameter code-retriever. |
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+ | [trumancai/Revela-code-500M](https://huggingface.co/trumancai/Revela-code-500M) | 500 M-parameter code-retriever. |
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+ | [trumancai/Revela-3b](https://huggingface.co/trumancai/Revela-3b) | 3 B-parameter Wikipedia retriever. |
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+ | [trumancai/Revela-1b](https://huggingface.co/trumancai/Revela-1b) | 1 B-parameter Wikipedia retriever. |
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+ | [trumancai/Revela-500M](https://huggingface.co/trumancai/Revela-500M) | 500 M-parameter Wikipedia retriever. |
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+ | [trumancai/revela_code_training_corpus](https://huggingface.co/datasets/trumancai/revela_code_training_corpus) | Code training corpus. |
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+ | [trumancai/revela_training_corpus](https://huggingface.co/datasets/trumancai/revela_training_corpus) | Wikipedia training corpus. |
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+
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+ # Usage
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+ ```python
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+ from mteb.model_meta import ModelMeta
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+ from mteb.models.repllama_models import RepLLaMAWrapper, _loader
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+ import mteb, torch
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+
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+ revela_code_llama_1b = ModelMeta(
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+ loader=_loader(
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+ RepLLaMAWrapper,
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+ base_model_name_or_path="meta-llama/Llama-3.2-1B",
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+ peft_model_name_or_path="trumancai/Revela-code-1b",
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+ device_map="auto",
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+ torch_dtype=torch.bfloat16,
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+ ),
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+ name="trumancai/Revela-code-1b",
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+ languages=["eng_Latn"],
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+ open_source=True,
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+ revision="564997a2d9b1132085aa7906b0e89e9802fffee8",
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+ release_date="2025-04-13",
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+ )
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+ model = revela_code_llama_1b.loader()
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+
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+ mteb.MTEB(tasks=["AppsRetrieval"])
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+ .run(model=model, output_folder="results/Revela-code-1b")
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+ ```
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+
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+ # License
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+
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+ # Citation