Instructions to use heitorrosa/logun-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use heitorrosa/logun-base with PEFT:
Task type is invalid.
- Transformers
How to use heitorrosa/logun-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="heitorrosa/logun-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("heitorrosa/logun-base") model = AutoModelForMaskedLM.from_pretrained("heitorrosa/logun-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- sft/checkpoint-450/README.md +206 -0
- sft/checkpoint-450/optimizer.pt +3 -0
- sft/checkpoint-450/rng_state_0.pth +3 -0
- sft/checkpoint-450/scaler.pt +3 -0
- sft/checkpoint-450/scheduler.pt +3 -0
- sft/checkpoint-450/sft/adapter_config.json +50 -0
- sft/checkpoint-450/sft/adapter_model.safetensors +3 -0
- sft/checkpoint-450/tokenizer.json +0 -0
- sft/checkpoint-450/tokenizer_config.json +19 -0
- sft/checkpoint-450/trainer_state.json +274 -0
- sft/checkpoint-450/training_args.bin +3 -0
sft/checkpoint-450/README.md
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| 1 |
+
---
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| 2 |
+
base_model: heitorrosa/logun-base
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library_name: peft
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tags:
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- base_model:adapter:heitorrosa/logun-base
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- lora
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- transformers
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---
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| 9 |
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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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| 22 |
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- **Developed by:** [More Information Needed]
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- **Funded by [optional]:** [More Information Needed]
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| 26 |
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- **Shared by [optional]:** [More Information Needed]
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| 27 |
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- **Model type:** [More Information Needed]
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| 28 |
+
- **Language(s) (NLP):** [More Information Needed]
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| 29 |
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- **License:** [More Information Needed]
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| 30 |
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- **Finetuned from model [optional]:** [More Information Needed]
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| 31 |
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+
### Model Sources [optional]
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| 33 |
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| 34 |
+
<!-- Provide the basic links for the model. -->
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| 36 |
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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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| 39 |
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| 40 |
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## Uses
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| 42 |
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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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| 43 |
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### Direct Use
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| 45 |
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| 46 |
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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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| 47 |
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[More Information Needed]
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| 49 |
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| 50 |
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### Downstream Use [optional]
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| 51 |
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| 52 |
+
<!-- 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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| 53 |
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| 54 |
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[More Information Needed]
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| 55 |
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|
| 56 |
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### Out-of-Scope Use
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| 57 |
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| 58 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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| 59 |
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| 60 |
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[More Information Needed]
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| 61 |
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| 62 |
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## Bias, Risks, and Limitations
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| 63 |
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| 64 |
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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| 66 |
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[More Information Needed]
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| 67 |
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| 68 |
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### Recommendations
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| 69 |
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| 70 |
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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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| 73 |
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## How to Get Started with the Model
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| 75 |
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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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| 81 |
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### Training Data
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| 83 |
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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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| 114 |
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| 115 |
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<!-- This should link to a Dataset Card if possible. -->
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| 117 |
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[More Information Needed]
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| 118 |
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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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| 124 |
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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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| 146 |
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| 147 |
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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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| 148 |
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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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| 152 |
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- **Hours used:** [More Information Needed]
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| 153 |
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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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### Framework versions
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- PEFT 0.20.0
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sft/checkpoint-450/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:c82ba4cdd55f7776c24cb08da2ec9abe37b0fde1b70cb4ed7e69ace78574cd97
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size 27204427
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sft/checkpoint-450/rng_state_0.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:6af6b4c42062851407670c78c1ae4e4d4d06397d777af4c3d0605817fbf30b70
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size 14917
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sft/checkpoint-450/scaler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:d028fbcacc64b27dda5ea74554be30b9d32fd7b72345a3b425d5a33df7e6494a
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size 1383
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sft/checkpoint-450/scheduler.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:2c8a15b5205d2ffe1c5a3b2faea5aa1e62bd38e026b21b84500f785c5ffc530c
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size 1465
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sft/checkpoint-450/sft/adapter_config.json
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{
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| 2 |
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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| 4 |
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"arrow_config": null,
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| 5 |
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"auto_mapping": null,
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| 6 |
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"base_model_name_or_path": "heitorrosa/logun-base",
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| 7 |
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"bias": "none",
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| 8 |
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"corda_config": null,
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| 9 |
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"ensure_weight_tying": false,
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| 10 |
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"eva_config": null,
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| 11 |
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"exclude_modules": null,
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| 12 |
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"fan_in_fan_out": false,
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| 13 |
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"inference_mode": true,
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| 14 |
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"init_lora_weights": true,
|
| 15 |
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"layer_replication": null,
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| 16 |
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"layers_pattern": null,
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| 17 |
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"layers_to_transform": null,
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| 18 |
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"loftq_config": {},
|
| 19 |
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"lora_alpha": 32,
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| 20 |
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"lora_bias": false,
|
| 21 |
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"lora_dropout": 0.05,
|
| 22 |
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"lora_ga_config": null,
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| 23 |
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"megatron_config": null,
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| 24 |
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"megatron_core": "megatron.core",
|
| 25 |
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"modules_to_save": [
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| 26 |
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"classifier",
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| 27 |
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"classifier",
|
| 28 |
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"score"
|
| 29 |
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],
|
| 30 |
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"monteclora_config": null,
|
| 31 |
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"peft_type": "LORA",
|
| 32 |
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"peft_version": "0.20.0",
|
| 33 |
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"qalora_group_size": 16,
|
| 34 |
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"r": 16,
|
| 35 |
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"rank_pattern": {},
|
| 36 |
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"revision": null,
|
| 37 |
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"target_modules": [
|
| 38 |
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"Wqkv",
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| 39 |
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"Wo",
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| 40 |
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"Wi"
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| 41 |
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],
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| 42 |
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"target_parameters": null,
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| 43 |
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"task_type": "SEQ_CLS",
|
| 44 |
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"trainable_token_indices": null,
|
| 45 |
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"use_bdlora": null,
|
| 46 |
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"use_dora": false,
|
| 47 |
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"use_qalora": false,
|
| 48 |
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"use_rslora": false,
|
| 49 |
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sft/checkpoint-450/training_args.bin
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@@ -0,0 +1,3 @@
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