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Model: suneater003/Aura-Merged-V1 Source: Original Platform
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199
README.md
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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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4
chat_template.jinja
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chat_template.jinja
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{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '
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' + message['content'] | trim + '<end_of_turn>
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' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model
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'}}{% endif %}
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68
config.json
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config.json
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{
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"architectures": [
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"Gemma2ForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"attn_logit_softcapping": 50.0,
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"bos_token_id": 2,
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"cache_implementation": "hybrid",
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"dtype": "float16",
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"eos_token_id": [
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1,
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107
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],
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"final_logit_softcapping": 30.0,
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"head_dim": 256,
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"hidden_act": "gelu_pytorch_tanh",
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"hidden_activation": "gelu_pytorch_tanh",
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"hidden_size": 2304,
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"initializer_range": 0.02,
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"intermediate_size": 9216,
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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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],
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"max_position_embeddings": 8192,
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"model_type": "gemma2",
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"num_attention_heads": 8,
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"num_hidden_layers": 26,
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"num_key_value_heads": 4,
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"pad_token_id": 0,
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"query_pre_attn_scalar": 256,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"rope_theta": 10000.0,
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"rope_type": "default"
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},
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"sliding_window": 4096,
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"tie_word_embeddings": true,
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"transformers_version": "5.0.0",
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"use_bidirectional_attention": null,
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"use_cache": true,
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"vocab_size": 256000
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}
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generation_config.json
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 2,
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"cache_implementation": "hybrid",
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"eos_token_id": [
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1,
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107
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],
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"pad_token_id": 0,
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"transformers_version": "5.0.0"
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}
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3
model.safetensors
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:769a048b4061d0e453b69b83c7f891255ea923d454d649514b622bf3ce15ebd3
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size 5228717224
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tokenizer.json
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:394ace002a144ac6ad5486387502f2d36f70c087310c3d907857240c76fcb36e
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size 34362748
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tokenizer_config.json
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tokenizer_config.json
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{
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"backend": "tokenizers",
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"bos_token": "<bos>",
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"clean_up_tokenization_spaces": false,
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"eos_token": "<eos>",
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"extra_special_tokens": [
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"<start_of_turn>",
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"<end_of_turn>"
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],
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"is_local": false,
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"mask_token": "<mask>",
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"sp_model_kwargs": {},
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"spaces_between_special_tokens": false,
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"tokenizer_class": "GemmaTokenizer",
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"unk_token": "<unk>",
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"use_default_system_prompt": false
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}
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