Instructions to use taskruy1/20267886-6020-40ed-bca4-afda97b28f37 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use taskruy1/20267886-6020-40ed-bca4-afda97b28f37 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-135M") model = PeftModel.from_pretrained(base_model, "taskruy1/20267886-6020-40ed-bca4-afda97b28f37") - Transformers
How to use taskruy1/20267886-6020-40ed-bca4-afda97b28f37 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="taskruy1/20267886-6020-40ed-bca4-afda97b28f37")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("taskruy1/20267886-6020-40ed-bca4-afda97b28f37", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use taskruy1/20267886-6020-40ed-bca4-afda97b28f37 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "taskruy1/20267886-6020-40ed-bca4-afda97b28f37" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "taskruy1/20267886-6020-40ed-bca4-afda97b28f37", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/taskruy1/20267886-6020-40ed-bca4-afda97b28f37
- SGLang
How to use taskruy1/20267886-6020-40ed-bca4-afda97b28f37 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "taskruy1/20267886-6020-40ed-bca4-afda97b28f37" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "taskruy1/20267886-6020-40ed-bca4-afda97b28f37", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "taskruy1/20267886-6020-40ed-bca4-afda97b28f37" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "taskruy1/20267886-6020-40ed-bca4-afda97b28f37", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Studio
How to use taskruy1/20267886-6020-40ed-bca4-afda97b28f37 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for taskruy1/20267886-6020-40ed-bca4-afda97b28f37 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for taskruy1/20267886-6020-40ed-bca4-afda97b28f37 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for taskruy1/20267886-6020-40ed-bca4-afda97b28f37 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="taskruy1/20267886-6020-40ed-bca4-afda97b28f37", max_seq_length=2048, ) - Docker Model Runner
How to use taskruy1/20267886-6020-40ed-bca4-afda97b28f37 with Docker Model Runner:
docker model run hf.co/taskruy1/20267886-6020-40ed-bca4-afda97b28f37
Training in progress, step 50, checkpoint
Browse files- last-checkpoint/README.md +208 -0
- last-checkpoint/adapter_config.json +41 -0
- last-checkpoint/adapter_model.safetensors +3 -0
- last-checkpoint/added_tokens.json +3 -0
- last-checkpoint/merges.txt +0 -0
- last-checkpoint/optimizer.pt +3 -0
- last-checkpoint/rng_state.pth +3 -0
- last-checkpoint/scheduler.pt +3 -0
- last-checkpoint/special_tokens_map.json +43 -0
- last-checkpoint/tokenizer.json +0 -0
- last-checkpoint/tokenizer_config.json +186 -0
- last-checkpoint/trainer_state.json +384 -0
- last-checkpoint/training_args.bin +3 -0
- last-checkpoint/vocab.json +0 -0
last-checkpoint/README.md
ADDED
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| 1 |
+
---
|
| 2 |
+
base_model: unsloth/SmolLM2-135M
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| 3 |
+
library_name: peft
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| 4 |
+
pipeline_tag: text-generation
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| 5 |
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tags:
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| 6 |
+
- base_model:adapter:unsloth/SmolLM2-135M
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| 7 |
+
- lora
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| 8 |
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- transformers
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| 9 |
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- unsloth
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| 10 |
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---
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| 11 |
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| 12 |
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# Model Card for Model ID
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| 13 |
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| 14 |
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<!-- Provide a quick summary of what the model is/does. -->
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| 15 |
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| 16 |
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| 18 |
+
## Model Details
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| 19 |
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### Model Description
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| 21 |
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<!-- Provide a longer summary of what this model is. -->
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| 23 |
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| 24 |
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| 25 |
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| 26 |
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- **Developed by:** [More Information Needed]
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| 27 |
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- **Funded by [optional]:** [More Information Needed]
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| 28 |
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- **Shared by [optional]:** [More Information Needed]
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| 29 |
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- **Model type:** [More Information Needed]
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| 30 |
+
- **Language(s) (NLP):** [More Information Needed]
|
| 31 |
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- **License:** [More Information Needed]
|
| 32 |
+
- **Finetuned from model [optional]:** [More Information Needed]
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| 33 |
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| 34 |
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### Model Sources [optional]
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| 35 |
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| 36 |
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<!-- Provide the basic links for the model. -->
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| 37 |
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| 38 |
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- **Repository:** [More Information Needed]
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| 39 |
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- **Paper [optional]:** [More Information Needed]
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| 40 |
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- **Demo [optional]:** [More Information Needed]
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| 41 |
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| 42 |
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## Uses
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| 43 |
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| 44 |
+
<!-- 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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| 45 |
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| 46 |
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### Direct Use
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| 47 |
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| 48 |
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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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| 49 |
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|
| 50 |
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[More Information Needed]
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| 51 |
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| 52 |
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### Downstream Use [optional]
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| 53 |
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| 54 |
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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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| 55 |
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| 56 |
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[More Information Needed]
|
| 57 |
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|
| 58 |
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### Out-of-Scope Use
|
| 59 |
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|
| 60 |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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| 61 |
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| 62 |
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[More Information Needed]
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| 63 |
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| 64 |
+
## Bias, Risks, and Limitations
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| 65 |
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| 66 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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| 67 |
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| 68 |
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[More Information Needed]
|
| 69 |
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| 70 |
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### Recommendations
|
| 71 |
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| 72 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
| 73 |
+
|
| 74 |
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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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| 75 |
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|
| 76 |
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## How to Get Started with the Model
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| 77 |
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| 78 |
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Use the code below to get started with the model.
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| 79 |
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| 80 |
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[More Information Needed]
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| 82 |
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## Training Details
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| 83 |
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| 84 |
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### Training Data
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| 85 |
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| 86 |
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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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| 92 |
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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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| 100 |
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| 101 |
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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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| 105 |
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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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| 115 |
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#### Testing Data
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| 116 |
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| 117 |
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<!-- This should link to a Dataset Card if possible. -->
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| 119 |
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[More Information Needed]
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| 120 |
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#### Factors
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| 122 |
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| 123 |
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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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| 126 |
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| 127 |
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#### Metrics
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| 128 |
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| 129 |
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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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| 133 |
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### Results
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[More Information Needed]
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| 136 |
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| 137 |
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#### Summary
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| 138 |
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| 139 |
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| 140 |
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## Model Examination [optional]
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| 142 |
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| 143 |
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<!-- Relevant interpretability work for the model goes here -->
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| 144 |
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| 145 |
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[More Information Needed]
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| 146 |
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| 147 |
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## Environmental Impact
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| 148 |
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| 149 |
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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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| 150 |
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| 151 |
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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).
|
| 152 |
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| 153 |
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- **Hardware Type:** [More Information Needed]
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| 154 |
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- **Hours used:** [More Information Needed]
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| 155 |
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- **Cloud Provider:** [More Information Needed]
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| 156 |
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- **Compute Region:** [More Information Needed]
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| 157 |
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- **Carbon Emitted:** [More Information Needed]
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| 158 |
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| 159 |
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## Technical Specifications [optional]
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| 160 |
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| 161 |
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### Model Architecture and Objective
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| 162 |
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| 163 |
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[More Information Needed]
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| 164 |
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| 165 |
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### Compute Infrastructure
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| 166 |
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| 167 |
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[More Information Needed]
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| 168 |
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| 169 |
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#### Hardware
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| 170 |
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| 171 |
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[More Information Needed]
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| 172 |
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| 173 |
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#### Software
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| 174 |
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[More Information Needed]
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| 176 |
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| 177 |
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## Citation [optional]
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| 178 |
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| 179 |
+
<!-- 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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| 180 |
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| 181 |
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**BibTeX:**
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| 182 |
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| 183 |
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[More Information Needed]
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| 184 |
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| 185 |
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**APA:**
|
| 186 |
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| 187 |
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[More Information Needed]
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| 188 |
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| 189 |
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## Glossary [optional]
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| 190 |
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| 191 |
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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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| 192 |
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| 193 |
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[More Information Needed]
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| 194 |
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| 195 |
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## More Information [optional]
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| 196 |
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[More Information Needed]
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| 198 |
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## Model Card Authors [optional]
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| 200 |
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[More Information Needed]
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| 202 |
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| 203 |
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## Model Card Contact
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| 204 |
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| 205 |
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[More Information Needed]
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| 206 |
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### Framework versions
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| 207 |
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| 208 |
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- PEFT 0.16.0
|
last-checkpoint/adapter_config.json
ADDED
|
@@ -0,0 +1,41 @@
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| 1 |
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{
|
| 2 |
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"alpha_pattern": {},
|
| 3 |
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"auto_mapping": null,
|
| 4 |
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"base_model_name_or_path": "unsloth/SmolLM2-135M",
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| 5 |
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"bias": "none",
|
| 6 |
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"corda_config": null,
|
| 7 |
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"eva_config": null,
|
| 8 |
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"exclude_modules": null,
|
| 9 |
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"fan_in_fan_out": false,
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| 10 |
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"inference_mode": true,
|
| 11 |
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"init_lora_weights": true,
|
| 12 |
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"layer_replication": null,
|
| 13 |
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"layers_pattern": null,
|
| 14 |
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"layers_to_transform": null,
|
| 15 |
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"loftq_config": {},
|
| 16 |
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"lora_alpha": 1024,
|
| 17 |
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"lora_bias": false,
|
| 18 |
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"lora_dropout": 0.0,
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| 19 |
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"megatron_config": null,
|
| 20 |
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