Instructions to use rovdetection/code-1b-expert-assistant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rovdetection/code-1b-expert-assistant with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("rovdetection/code-1b-expert-assistant", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000, checkpoint
Browse files- last-checkpoint/README.md +209 -0
- last-checkpoint/adapter_config.json +48 -0
- last-checkpoint/adapter_model.safetensors +3 -0
- last-checkpoint/optimizer.pt +3 -0
- last-checkpoint/rng_state_0.pth +3 -0
- last-checkpoint/rng_state_1.pth +3 -0
- last-checkpoint/scaler.pt +3 -0
- last-checkpoint/scheduler.pt +3 -0
- last-checkpoint/tokenizer.json +0 -0
- last-checkpoint/tokenizer_config.json +13 -0
- last-checkpoint/trainer_state.json +234 -0
- last-checkpoint/training_args.bin +3 -0
last-checkpoint/README.md
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| 1 |
+
---
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| 2 |
+
base_model: rovdetection/code-1b-pretrain
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| 3 |
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library_name: peft
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| 4 |
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pipeline_tag: text-generation
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tags:
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- base_model:adapter:rovdetection/code-1b-pretrain
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| 7 |
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- lora
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| 8 |
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- sft
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| 9 |
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- transformers
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| 10 |
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- trl
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| 11 |
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---
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| 12 |
+
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| 13 |
+
# Model Card for Model ID
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| 14 |
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| 15 |
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<!-- Provide a quick summary of what the model is/does. -->
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| 16 |
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| 17 |
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| 18 |
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| 19 |
+
## Model Details
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| 20 |
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| 21 |
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### Model Description
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| 22 |
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| 23 |
+
<!-- Provide a longer summary of what this model is. -->
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| 24 |
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| 25 |
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| 26 |
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| 27 |
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- **Developed by:** [More Information Needed]
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| 28 |
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- **Funded by [optional]:** [More Information Needed]
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| 29 |
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- **Shared by [optional]:** [More Information Needed]
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| 30 |
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- **Model type:** [More Information Needed]
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| 31 |
+
- **Language(s) (NLP):** [More Information Needed]
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| 32 |
+
- **License:** [More Information Needed]
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| 33 |
+
- **Finetuned from model [optional]:** [More Information Needed]
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| 34 |
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| 35 |
+
### Model Sources [optional]
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| 36 |
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| 37 |
+
<!-- Provide the basic links for the model. -->
|
| 38 |
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| 39 |
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- **Repository:** [More Information Needed]
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| 40 |
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- **Paper [optional]:** [More Information Needed]
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| 41 |
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- **Demo [optional]:** [More Information Needed]
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| 42 |
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| 43 |
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## Uses
|
| 44 |
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| 45 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
| 46 |
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|
| 47 |
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### Direct Use
|
| 48 |
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|
| 49 |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
| 50 |
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|
| 51 |
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[More Information Needed]
|
| 52 |
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|
| 53 |
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### Downstream Use [optional]
|
| 54 |
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|
| 55 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
| 56 |
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|
| 57 |
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[More Information Needed]
|
| 58 |
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|
| 59 |
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### Out-of-Scope Use
|
| 60 |
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|
| 61 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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| 62 |
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| 63 |
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[More Information Needed]
|
| 64 |
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|
| 65 |
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## Bias, Risks, and Limitations
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| 66 |
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|
| 67 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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| 68 |
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| 69 |
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[More Information Needed]
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| 70 |
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|
| 71 |
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### Recommendations
|
| 72 |
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| 73 |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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| 74 |
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|
| 75 |
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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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| 76 |
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| 77 |
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## How to Get Started with the Model
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| 78 |
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| 79 |
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Use the code below to get started with the model.
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| 80 |
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| 81 |
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[More Information Needed]
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| 83 |
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## Training Details
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| 84 |
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|
| 85 |
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### Training Data
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| 86 |
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| 87 |
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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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| 88 |
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[More Information Needed]
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| 91 |
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### Training Procedure
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| 92 |
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|
| 93 |
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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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| 94 |
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#### Preprocessing [optional]
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| 96 |
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| 97 |
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[More Information Needed]
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| 99 |
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|
| 100 |
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#### Training Hyperparameters
|
| 101 |
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|
| 102 |
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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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| 103 |
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| 104 |
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#### Speeds, Sizes, Times [optional]
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| 105 |
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| 106 |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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| 107 |
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| 108 |
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[More Information Needed]
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| 109 |
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| 110 |
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## Evaluation
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| 111 |
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| 112 |
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<!-- This section describes the evaluation protocols and provides the results. -->
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| 114 |
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### Testing Data, Factors & Metrics
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| 115 |
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| 116 |
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#### Testing Data
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| 117 |
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|
| 118 |
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<!-- This should link to a Dataset Card if possible. -->
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| 119 |
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| 120 |
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[More Information Needed]
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| 121 |
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| 122 |
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#### Factors
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| 123 |
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| 124 |
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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| 125 |
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| 126 |
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[More Information Needed]
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| 127 |
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|
| 128 |
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#### Metrics
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| 129 |
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| 130 |
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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| 131 |
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| 132 |
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[More Information Needed]
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| 133 |
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### Results
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| 135 |
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[More Information Needed]
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| 137 |
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| 138 |
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#### Summary
|
| 139 |
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| 140 |
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| 141 |
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| 142 |
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## Model Examination [optional]
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| 143 |
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| 144 |
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<!-- Relevant interpretability work for the model goes here -->
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| 145 |
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| 146 |
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[More Information Needed]
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| 147 |
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| 148 |
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## Environmental Impact
|
| 149 |
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| 150 |
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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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| 151 |
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| 152 |
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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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| 153 |
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| 154 |
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- **Hardware Type:** [More Information Needed]
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| 155 |
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- **Hours used:** [More Information Needed]
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| 156 |
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- **Cloud Provider:** [More Information Needed]
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| 157 |
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- **Compute Region:** [More Information Needed]
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| 158 |
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- **Carbon Emitted:** [More Information Needed]
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| 159 |
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| 160 |
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## Technical Specifications [optional]
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| 161 |
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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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| 167 |
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[More Information Needed]
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| 169 |
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#### Hardware
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| 171 |
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| 172 |
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[More Information Needed]
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| 173 |
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#### Software
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| 175 |
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[More Information Needed]
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## Citation [optional]
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| 179 |
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| 180 |
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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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| 181 |
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| 182 |
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**BibTeX:**
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| 183 |
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| 184 |
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[More Information Needed]
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| 185 |
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| 186 |
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**APA:**
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| 187 |
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| 188 |
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[More Information Needed]
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| 189 |
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|
| 190 |
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## Glossary [optional]
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| 191 |
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|
| 192 |
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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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| 193 |
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| 194 |
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[More Information Needed]
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| 195 |
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## More Information [optional]
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| 197 |
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[More Information Needed]
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| 199 |
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## Model Card Authors [optional]
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| 201 |
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| 202 |
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[More Information Needed]
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| 203 |
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## Model Card Contact
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| 205 |
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| 206 |
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[More Information Needed]
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| 207 |
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### Framework versions
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| 208 |
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| 209 |
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- PEFT 0.19.1
|
last-checkpoint/adapter_config.json
ADDED
|
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| 1 |
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{
|
| 2 |
+
"alora_invocation_tokens": null,
|
| 3 |
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"alpha_pattern": {},
|
| 4 |
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"arrow_config": null,
|
| 5 |
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"auto_mapping": null,
|
| 6 |
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"base_model_name_or_path": "rovdetection/code-1b-pretrain",
|
| 7 |
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"bias": "none",
|
| 8 |
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"corda_config": null,
|
| 9 |
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"ensure_weight_tying": false,
|
| 10 |
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"eva_config": null,
|
| 11 |
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"exclude_modules": null,
|
| 12 |
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"fan_in_fan_out": false,
|
| 13 |
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"inference_mode": true,
|
| 14 |
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"init_lora_weights": true,
|
| 15 |
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"layer_replication": null,
|
| 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": 256,
|
| 20 |
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"lora_bias": false,
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| 21 |
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"lora_dropout": 0.05,
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| 22 |
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"lora_ga_config": null,
|
| 23 |
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"megatron_config": null,
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| 24 |
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"megatron_core": "megatron.core",
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| 25 |
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"modules_to_save": null,
|
| 26 |
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"peft_type": "LORA",
|
| 27 |
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"peft_version": "0.19.1",
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| 28 |
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"qalora_group_size": 16,
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| 29 |
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"r": 128,
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| 30 |
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"rank_pattern": {},
|
| 31 |
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"revision": null,
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| 32 |
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"target_modules": [
|
| 33 |
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"v_proj",
|
| 34 |
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"gate_proj",
|
| 35 |
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"up_proj",
|
| 36 |
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"down_proj",
|
| 37 |
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"k_proj",
|
| 38 |
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"q_proj",
|
| 39 |
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"o_proj"
|
| 40 |
+
],
|
| 41 |
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"target_parameters": null,
|
| 42 |
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"task_type": "CAUSAL_LM",
|
| 43 |
+
"trainable_token_indices": null,
|
| 44 |
+
"use_bdlora": null,
|
| 45 |
+
"use_dora": false,
|
| 46 |
+
"use_qalora": false,
|
| 47 |
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"use_rslora": false
|
| 48 |
+
}
|
last-checkpoint/adapter_model.safetensors
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:bbc31def6fc1183573b4ca53bf82830b3e675c174bc8741079dee8f82ace3c3d
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size 363365712
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last-checkpoint/optimizer.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:618454c138b7364f8dc01f3db6c85573dc0fe52fe5fefec5e12a9d9ba2f00f2f
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size 184804245
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last-checkpoint/rng_state_0.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:35b6d066bf9203e4799e272b55e9f98b2cb902bb50e8ac3a00afbb0a5d66b1fd
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size 14917
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last-checkpoint/rng_state_1.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:3ab50382464f53407058d665fe007033934f3cde6d503d0d5554e6d5a2642329
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size 14917
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last-checkpoint/scaler.pt
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"train_batch_size": 2,
|
| 232 |
+
"trial_name": null,
|
| 233 |
+
"trial_params": null
|
| 234 |
+
}
|
last-checkpoint/training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:72d5d698823ff3855f1b14a90837b64ecd809efa1725d828f6c4a6ff29924a83
|
| 3 |
+
size 5777
|