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  1. README.md +199 -0
  2. config.json +53 -0
  3. g_retriever_config.py +31 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ tags: []
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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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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+
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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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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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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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+
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+ ## Uses
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+
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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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+ ### Direct Use
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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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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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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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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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Training Procedure
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+
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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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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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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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+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
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+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
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+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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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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+
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+ #### Summary
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+
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+
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+ ## Model Examination [optional]
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+
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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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+
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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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+
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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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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+ [More Information Needed]
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+
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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]
config.json ADDED
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+ {
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+ "_name_or_path": "NousResearch/Hermes-3-Llama-3.1-8B",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "auto_map": {
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+ "AutoConfig": "g_retriever_config.GRetrieverConfig"
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+ },
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+ "bos_id": [
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+ 128000,
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+ 128000,
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+ 128006,
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+ 882,
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+ 128007
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+ ],
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+ "bos_token_id": 128000,
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+ "eos_token_id": 128040,
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+ "gnn_dropout": 0,
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+ "gnn_hidden_dim": 1024,
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+ "gnn_in_dim": 768,
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+ "gnn_num_heads": 4,
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+ "gnn_num_layers": 4,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_new_tokens": 256,
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+ "max_position_embeddings": 131072,
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+ "max_txt_len": 1024,
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+ "mlp_bias": false,
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+ "model_type": "llama",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
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+ "pad_token_id": 128040,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": {
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+ "factor": 8.0,
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+ "high_freq_factor": 4.0,
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+ "low_freq_factor": 1.0,
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+ "original_max_position_embeddings": 8192,
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+ "rope_type": "llama3"
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+ },
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+ "rope_theta": 500000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.44.0",
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+ "use_cache": true,
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+ "vocab_size": 128256
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+ }
g_retriever_config.py ADDED
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+ from transformers import LlamaConfig
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+
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+ class GRetrieverConfig(LlamaConfig):
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+ model_type = "llama"
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+
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+ def __init__(
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+ self,
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+ max_txt_len: int = 1024,
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+ max_new_tokens: int = 256,
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+ gnn_num_layers: int = 4,
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+ gnn_in_dim: int = 768,
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+ gnn_hidden_dim: int = 1024,
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+ gnn_num_heads: int = 4,
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+ gnn_dropout: int = 0,
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+ bos_id: list = [128000, 128000, 128006, 882, 128007],
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+ **kwargs
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+ ):
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+ pretrained_config = LlamaConfig.from_pretrained("NousResearch/Hermes-3-Llama-3.1-8B")
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+ pretrained_config.update(kwargs)
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+
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+ self.max_txt_len = max_txt_len
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+ self.max_new_tokens = max_new_tokens
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+ self.gnn_num_layers = gnn_num_layers
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+ self.gnn_in_dim = gnn_in_dim
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+ self.gnn_hidden_dim = gnn_hidden_dim
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+ self.gnn_num_heads = gnn_num_heads
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+ self.gnn_dropout = gnn_dropout
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+ self.bos_id = bos_id
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+
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+ super().__init__(**pretrained_config.to_dict())
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+ self.pad_token_id = pretrained_config.eos_token_id