SentenceTransformer(
(0): Transformer({'transformer_task': 'feature-extraction', 'modality_config': {'text': {'method': 'forward', 'method_output_name': 'last_hidden_state'}}, 'module_output_name': 'token_embeddings', 'architecture': 'MPNetModel'})
(1): Pooling({'embedding_dimension': 768, 'pooling_mode': 'mean', 'include_prompt': True})
(2): Normalize({})
)pip install -U sentence-transformers1from sentence_transformers import SentenceTransformer
2
3# Download from the 🤗 Hub
4model = SentenceTransformer("sentence_transformers_model_id")
5# Run inference
6sentences = [
7 'Unity Development. Game Development. Mobile Game Development. Game Design. Game Art. 2D Game Art. 3D Game Art. 3D Modeling. Level Design. Game Prototype. Game UI/UX Design. Augmented Reality. Virtual Reality. Animation. VFX. Game Documentation. Game Balance. Analytics Integration. Monetization Strategy. User Acquisition. Unity. Unity Game Development. Creates full-cycle 2D and 3D mobile games from concept to launch and support.. Game Art and UI/UX. Designs 2D/3D art assets, animations, VFX, and user interfaces for games.. Game Design and Monetization. Builds GDDs, wireframes, balance systems, analytics integration, and monetization features.. Senior Game Development Expert | Mind Studios. Works on full-cycle development of 2D and 3D mobile games, from idea to launch and support (September 2016 - Present).',
8 'Machine Learning Engineer\n\n Requirements:\n Python, Machine Learning, Deep Learning,\n NLP, TensorFlow, PyTorch, SQL,\n Data Science, Artificial Intelligence,\n Generative AI, Transformers.',
9 'Machine Learning Engineer\n\n Requirements:\n Python, Machine Learning, Deep Learning,\n NLP, TensorFlow, PyTorch, SQL,\n Data Science, Artificial Intelligence,\n Generative AI, Transformers.',
10]
11embeddings = model.encode(sentences)
12print(embeddings.shape)
13# [3, 768]
14
15# Get the similarity scores for the embeddings
16similarities = model.similarity(embeddings, embeddings)
17print(similarities)
18# tensor([[1.0000, 0.0610, 0.0610],
19# [0.0610, 1.0000, 1.0000],
20# [0.0610, 1.0000, 1.0000]])sentence_0, sentence_1, and label| sentence_0 | sentence_1 | label | |
|---|---|---|---|
| type | string | string | float |
| modality | text | text | |
| details |
|
|
|
| sentence_0 | sentence_1 | label |
|---|---|---|
Program management. Cybersecurity. Risk assessment. Vulnerability management. Business continuity. Standardization. Policy and coordination. Web security. Adversary emulation. Adversary emulation services. Enterprise CIS security frameworks. Business continuity planning tools. Web Presence Security Program. Managed a NATO web presence security program to improve cybersecurity posture and implement adversary emulation services.. Enterprise CIS Security Initiatives. Led enterprise-wide CIS security coherence and vulnerability management activities to strengthen NATO security and resilience.. NATO Business Continuity Project. Coordinated business continuity activities to support NATO operational resilience during transitions.. Program Manager - NATO OCIO. Manage cybersecurity programs focused on ICT coherence, enterprise CIS security, vulnerability management, and adversary emulation (March 2022 - Present).. Business Continuity Project Coordinator - NATO. Coordinated business continuity p... | Cybersecurity Engineer[object Object][object Object] Requirements:[object Object] Network Security, Ethical Hacking,[object Object] Penetration Testing,[object Object] Vulnerability Assessment,[object Object] Python, Linux, Wireshark,[object Object] Nmap, SIEM,[object Object] Incident Response,[object Object] Digital Forensics. | 0.7298 |
Cloud Platform Engineering. DevOps. Site Reliability Engineering. Infrastructure as Code. CI/CD. Kubernetes. Docker. Cloud Migration. Observability. Security and Compliance. Terraform. Platform Architecture. Database / Data Platform. EKS. ECS. Lambda. VPC. IAM. RDS. S3. CloudWatch. CloudTrail. GuardDuty. API Gateway. AKS. Data Factory. Functions. Key Vault. Entra ID. Private Link. Azure Monitor. Terraform. Helm. Kustomize. Ansible. ArgoCD. Flux. GitHub Actions. GitLab CI. Azure DevOps. Jenkins. Prometheus. Grafana. ELK. Loki. OpenTelemetry. PagerDuty. Vault. OPA. Kyverno. Trivy. Snowflake. ADLS Gen2. Power BI. Python. Bash. YAML. HCL. On-prem to AWS Migration. Led phased zero-downtime migration from on-prem to AWS with multi-AZ EKS clusters, segmented VPCs, and modular Terraform reducing infrastructure drift by ~90%.. Cloud-native Platform with GitOps. Designed cloud-native platform using Kubernetes, ArgoCD, hardened CI/CD with image scanning and SAST, full observability, Vault secrets... | Machine Learning Engineer[object Object][object Object] Requirements:[object Object] Python, Machine Learning, Deep Learning,[object Object] NLP, TensorFlow, PyTorch, SQL,[object Object] Data Science, Artificial Intelligence,[object Object] Generative AI, Transformers. | 0.1524 |
Cyber resilience. Information security management. ISO 27001. Risk management. Security assessments. Gap analysis. CISO-as-a-Service. Project management. Customer success. Training and awareness. ISO/IEC 27001. NIST CSF. OneTrust (inferred from GRC tooling experience). M365. BSI IT-Grundschutz. ISMS Implementation and Audit. Led ISMS build, audits, security assessments and gap analyses aligned with ISO/IEC 27001 and NIST CSF to improve organisational security posture.. Regulatory Readiness for NIS2 & CRA. Advised clients on compliance and translated regulatory requirements (NIS2, Cyber Resilience Act, FINMA) into practical measures and governance.. M365 Rollout and OKR Adoption. Managed M365 rollout projects and introduced OKR agile management practices while coordinating project risks and stakeholder engagement.. Cyber Security Consultant - InfoGuard AG. Consulting on cyber security, ISMS implementation, audits, risk analyses and regulatory compliance including NIS2 and Cyber Resilien... | Cloud Engineer[object Object][object Object] Requirements:[object Object] AWS, Azure, Google Cloud,[object Object] Docker, Kubernetes,[object Object] Terraform, Linux,[object Object] DevOps, CI/CD,[object Object] Cloud Infrastructure,[object Object] Cloud Security. | 0.16920000000000002 |
CosineSimilarityLoss with these parameters:
1{
2 "loss_fct": "torch.nn.modules.loss.MSELoss",
3 "cos_score_transformation": "torch.nn.modules.linear.Identity"
4}per_device_train_batch_size: 16per_device_eval_batch_size: 16multi_dataset_batch_sampler: round_robinper_device_train_batch_size: 16num_train_epochs: 3max_steps: -1learning_rate: 5e-05lr_scheduler_type: linearlr_scheduler_kwargs: Nonewarmup_steps: 0optim: adamw_torch_fusedoptim_args: Noneweight_decay: 0.0adam_beta1: 0.9adam_beta2: 0.999adam_epsilon: 1e-08optim_target_modules: Nonegradient_accumulation_steps: 1average_tokens_across_devices: Truemax_grad_norm: 1label_smoothing_factor: 0.0bf16: Falsefp16: Falsebf16_full_eval: Falsefp16_full_eval: Falsetf32: Nonegradient_checkpointing: Falsegradient_checkpointing_kwargs: Nonetorch_compile: Falsetorch_compile_backend: Nonetorch_compile_mode: Noneuse_liger_kernel: Falseliger_kernel_config: Noneuse_cache: Falseneftune_noise_alpha: Nonetorch_empty_cache_steps: Noneauto_find_batch_size: Falselog_on_each_node: Truelogging_nan_inf_filter: Trueinclude_num_input_tokens_seen: nolog_level: passivelog_level_replica: warningdisable_tqdm: Falseproject: huggingfacetrackio_space_id: Nonetrackio_bucket_id: Nonetrackio_static_space_id: Noneper_device_eval_batch_size: 16prediction_loss_only: Trueeval_on_start: Falseeval_do_concat_batches: Trueeval_use_gather_object: Falseeval_accumulation_steps: Noneinclude_for_metrics: []batch_eval_metrics: Falsesave_only_model: Falsesave_on_each_node: Falseenable_jit_checkpoint: Falsepush_to_hub: Falsehub_private_repo: Nonehub_model_id: Nonehub_strategy: every_savehub_always_push: Falsehub_revision: Noneload_best_model_at_end: Falseignore_data_skip: Falserestore_callback_states_from_checkpoint: Falsefull_determinism: Falseseed: 42data_seed: Noneuse_cpu: Falseaccelerator_config: {'split_batches': False, 'dispatch_batches': None, 'even_batches': True, 'use_seedable_sampler': True, 'non_blocking': False, 'gradient_accumulation_kwargs': None}parallelism_config: Nonedataloader_drop_last: Falsedataloader_num_workers: 0dataloader_pin_memory: Truedataloader_persistent_workers: Falsedataloader_prefetch_factor: Noneremove_unused_columns: Truelabel_names: Nonetrain_sampling_strategy: randomlength_column_name: lengthddp_find_unused_parameters: Noneddp_bucket_cap_mb: Noneddp_broadcast_buffers: Falseddp_static_graph: Noneddp_backend: Noneddp_timeout: 1800fsdp: Nonefsdp_config: Nonedeepspeed: Nonedebug: []skip_memory_metrics: Truedo_predict: Falseresume_from_checkpoint: Nonewarmup_ratio: Nonelocal_rank: -1prompts: Nonebatch_sampler: batch_samplermulti_dataset_batch_sampler: round_robinrouter_mapping: {}learning_rate_mapping: {}| Epoch | Step | Training Loss |
|---|---|---|
| 2.7027 | 500 | 0.0031 |
1@inproceedings{reimers-2019-sentence-bert,
2 title = "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks",
3 author = "Reimers, Nils and Gurevych, Iryna",
4 booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing",
5 month = "11",
6 year = "2019",
7 publisher = "Association for Computational Linguistics",
8 url = "https://arxiv.org/abs/1908.10084",
9}