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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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-
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  ## Model Details
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@@ -15,15 +25,16 @@ tags: []
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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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@@ -41,7 +52,30 @@ This is the model card of a 🤗 transformers model that has been pushed on the
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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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@@ -75,11 +109,183 @@ Use the code below to get started with the model.
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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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@@ -89,10 +295,50 @@ Use the code below to get started with the model.
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  [More Information Needed]
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-
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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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@@ -196,4 +442,4 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
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  ## Model Card Contact
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- [More Information Needed]
 
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  ---
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+ # For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
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+ # Doc / guide: https://huggingface.co/docs/hub/model-cards
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+ base_model:
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+ - HuggingFaceTB/SmolLM-135M-Instruct
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+ datasets: []
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+ languages:
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+ - en
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  library_name: transformers
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+ metrics: []
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+ pipeline_tag: text-generation
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  tags: []
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+
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  ---
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+ # Model Card for ldp72/Test-SmolLM-Marcel
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  <!-- Provide a quick summary of what the model is/does. -->
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+ This model was finetuned by performing instruct tuning on Telco domain datatsets.
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  ## Model Details
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  <!-- Provide a longer summary of what this model is. -->
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+
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+ - **Developed by:** Orange
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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):** English
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  - **License:** [More Information Needed]
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+ - **Finetuned from model [optional]:** HuggingFaceTB/SmolLM-135M-Instruct
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+ - **Date [optional]:** 2025-07-18 09:48:27
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  ### Model Sources [optional]
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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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+
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+ This model can be used with the `transformers` library using `pipeline` abstraction as follows:
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+
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+ ```python
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+ import torch
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+ from transformers import pipeline
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+
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+ model_id = "ldp72/Test-SmolLM-Marcel"
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+ pipe = pipeline(
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+ "text-generation",
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+ model=model_id,
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+ torch_dtype=torch.bfloat16,
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+ device_map="auto",
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+ )
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+ messages = [
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+ {"role": "system", "content": "You are chatbot specialized on Telco domain."},
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+ {"role": "user", "content": "Can you give a sample of your specialized knowledge?"},
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+ ]
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+ outputs = pipe(
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+ messages,
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+ max_new_tokens=256,
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+ )
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+ print(outputs[0]["generated_text"][-1])
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+ ```
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  ### Downstream Use [optional]
81
 
 
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  ## Training Details
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+ This model was finetuned with [Orange internal fine tuning tools](https://gitlab.tech.orange/NEPAL/knowledge/orangelm/lm-adaptation/) with the Docker Image tagged `0.1.1` in the [registry](https://gitlab.tech.orange/NEPAL/knowledge/orangelm/lm-adaptation/container_registry/84664) and the following configuration file:
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+
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+ ```yaml
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+ data:
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+ dataset_name:
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+ train:
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+ - path: telco-lm/arxiv-abstract-generation-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-dsp.stackexchange.com-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-networkengineering.stackexchange.com-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-security.stackexchange.com-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-3gpp-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-5gamericas-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-huawei-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-itu-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-mef-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-ngmn-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-rfc-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/teleqna-mcqa-cot-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/tii-huawei-qa-open-qa-telco-instructions
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+ revision: legacy
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+ validation_abstract_generation:
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+ - path: telco-lm/arxiv-abstract-generation-telco-instructions
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+ revision: legacy
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+ split: validation
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+ validation_general:
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+ - path: telco-lm/slim-orca-multi-task-general-instructions
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+ revision: legacy
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+ split: validation
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+ validation_synthetic:
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+ - path: telco-lm/synthetic-dsp.stackexchange.com-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-security.stackexchange.com-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-networkengineering.stackexchange.com-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-technical-rfc-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-technical-3gpp-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-technical-5gamericas-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-technical-itu-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-technical-mef-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-technical-huawei-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ - path: telco-lm/synthetic-technical-ngmn-multi-task-telco-instructions
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+ revision: legacy
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+ split: validation
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+ validation_telco_qa:
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+ - path: telco-lm/tii-huawei-qa-open-qa-telco-instructions
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+ revision: legacy
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+ split: validation
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+ validation_telco_qcm:
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+ - path: telco-lm/teleqna-mcqa-cot-telco-instructions
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+ revision: legacy
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+ split: validation
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+ debug: true
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+ implementation_name: instructions
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+ description:
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+ contributors:
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+ - email: [email protected]
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+ first_name: Loïc
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+ last_name: Fosse
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+ - email: [email protected]
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+ first_name: Lionel
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+ last_name: Delphin-Poulat
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+ - email: [email protected]
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+ first_name: Ismaël
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+ last_name: Rousseau
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+ domain: Telco
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+ languages:
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+ - en
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+ model_name: ldp72/Test-SmolLM-Marcel
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+ image:
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+ version: 0.1.1
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+ model:
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+ attn_implementation: flash_attention_2
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+ chat_template_tokenizer: HuggingFaceTB/SmolLM-135M-Instruct
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+ model_name_or_path: HuggingFaceTB/SmolLM-135M-Instruct
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+ trust_remote_code: true
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+ training:
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+ bf16: true
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+ dataloader_num_workers: 4
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+ dataloader_persistent_workers: true
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+ dataloader_pin_memory: true
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+ dataloader_prefetch_factor: 2
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+ deepspeed: /config/zero3.json
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+ disable_tqdm: true
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+ eval_accumulation_steps: 1
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+ eval_steps: 10
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+ eval_strategy: steps
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+ fp16: false
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+ gradient_accumulation_steps: 2
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+ gradient_checkpointing: true
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+ group_by_length: false
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+ learning_rate: 2.0e-05
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+ log_level: debug
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+ logging_dir: /outputs/Telco-SmolLM-135-Instruct-it-non-reg/logs
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+ logging_steps: 10
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+ lr_scheduler_type: cosine
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+ max_grad_norm: 1.0
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+ max_steps: -1
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+ num_train_epochs: 2
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+ optim: paged_adamw_32bit
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+ output_dir: /outputs/Telco-SmolLM-135-Instruct-it-non-reg
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+ per_device_eval_batch_size: 2
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+ per_device_train_batch_size: 2
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+ push_to_hub: false
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+ report_to: tensorboard
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+ save_steps: 0
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+ save_strategy: epoch
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+ save_total_limit: 1
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+ seed: 42
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+ torch_compile: false
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+ training_type: instruct-tuning
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+ use_liger_kernel: false
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+ warmup_ratio: 0.05
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+ weight_decay: 0.1
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+ ```
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+
255
  ### Training Data
256
 
257
  <!-- 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. -->
258
 
259
+ This model was trained on the following datasets:
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+
261
+ ```yaml
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+ - path: telco-lm/arxiv-abstract-generation-telco-instructions
263
+ revision: legacy
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+ - path: telco-lm/synthetic-dsp.stackexchange.com-multi-task-telco-instructions
265
+ revision: legacy
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+ - path: telco-lm/synthetic-networkengineering.stackexchange.com-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-security.stackexchange.com-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-3gpp-multi-task-telco-instructions
271
+ revision: legacy
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+ - path: telco-lm/synthetic-technical-5gamericas-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-huawei-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/synthetic-technical-itu-multi-task-telco-instructions
277
+ revision: legacy
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+ - path: telco-lm/synthetic-technical-mef-multi-task-telco-instructions
279
+ revision: legacy
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+ - path: telco-lm/synthetic-technical-ngmn-multi-task-telco-instructions
281
+ revision: legacy
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+ - path: telco-lm/synthetic-technical-rfc-multi-task-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/teleqna-mcqa-cot-telco-instructions
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+ revision: legacy
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+ - path: telco-lm/tii-huawei-qa-open-qa-telco-instructions
287
+ revision: legacy
288
+ ```
289
 
290
  ### Training Procedure
291
 
 
295
 
296
  [More Information Needed]
297
 
 
298
  #### Training Hyperparameters
299
 
300
+ <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
301
+
302
+ - **Training regime:** This model was trained with the following hyperparameters for `SFTTrainer`,other parameters were set as default:
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+
304
+ ```yaml
305
+ bf16: true
306
+ dataloader_num_workers: 4
307
+ dataloader_persistent_workers: true
308
+ dataloader_pin_memory: true
309
+ dataloader_prefetch_factor: 2
310
+ deepspeed: /config/zero3.json
311
+ disable_tqdm: true
312
+ eval_accumulation_steps: 1
313
+ eval_steps: 10
314
+ eval_strategy: steps
315
+ fp16: false
316
+ gradient_accumulation_steps: 2
317
+ gradient_checkpointing: true
318
+ group_by_length: false
319
+ learning_rate: 2.0e-05
320
+ log_level: debug
321
+ logging_dir: /outputs/Telco-SmolLM-135-Instruct-it-non-reg/logs
322
+ logging_steps: 10
323
+ lr_scheduler_type: cosine
324
+ max_grad_norm: 1.0
325
+ max_steps: -1
326
+ num_train_epochs: 2
327
+ optim: paged_adamw_32bit
328
+ output_dir: /outputs/Telco-SmolLM-135-Instruct-it-non-reg
329
+ per_device_eval_batch_size: 2
330
+ per_device_train_batch_size: 2
331
+ push_to_hub: false
332
+ report_to: tensorboard
333
+ save_steps: 0
334
+ save_strategy: epoch
335
+ save_total_limit: 1
336
+ seed: 42
337
+ torch_compile: false
338
+ use_liger_kernel: false
339
+ warmup_ratio: 0.05
340
+ weight_decay: 0.1
341
+ ```
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343
  #### Speeds, Sizes, Times [optional]
344
 
 
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443
  ## Model Card Contact
444
 
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+ Thanks to [Loïc Fosse](mailto:[email protected]), [Lionel Delphin-Poulat](mailto:[email protected]), [Ismaël Rousseau](mailto:[email protected]) for adding this model.