Upload GptOssForCausalLM
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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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            - **Repository:** [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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            ### Out-of-Scope Use
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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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            [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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            [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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            [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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| 1 | 
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            {
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              "architectures": [
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                "GptOssForCausalLM"
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              ],
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              "attention_bias": true,
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              "attention_dropout": 0.0,
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              "eos_token_id": 200002,
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              "experts_per_token": 4,
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              "head_dim": 64,
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              "hidden_act": "silu",
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              "hidden_size": 2880,
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              "initial_context_length": 4096,
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              "initializer_range": 0.02,
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              "intermediate_size": 2880,
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              "layer_types": [
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention",
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                "sliding_attention",
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                "full_attention"
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              ],
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              "max_position_embeddings": 131072,
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              "model_type": "gpt_oss",
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              "num_attention_heads": 64,
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              "num_experts_per_tok": 4,
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              "num_hidden_layers": 36,
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              "num_key_value_heads": 8,
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              "num_local_experts": 128,
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              "output_router_logits": false,
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              "pad_token_id": 199999,
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              "quantization_config": {
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                "_load_in_4bit": true,
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                "_load_in_8bit": false,
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                "bnb_4bit_compute_dtype": "float16",
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                "bnb_4bit_quant_storage": "uint8",
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                "bnb_4bit_quant_type": "nf4",
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                "bnb_4bit_use_double_quant": true,
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                "llm_int8_enable_fp32_cpu_offload": false,
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                "llm_int8_has_fp16_weight": false,
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                "llm_int8_skip_modules": [
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                  "router",
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                  "embed_tokens",
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                  "lm_head"
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                ],
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                "llm_int8_threshold": 6.0,
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                "load_in_4bit": true,
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                "load_in_8bit": false,
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                "quant_method": "bitsandbytes"
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              },
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              "rms_norm_eps": 1e-05,
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            +
              "rope_scaling": {
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                "beta_fast": 32.0,
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| 84 | 
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