Sentence Similarity
sentence-transformers
Safetensors
qwen2
feature-extraction
Generated from Trainer
dataset_size:1580101
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use AlexWortega/qwen_emb_6k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AlexWortega/qwen_emb_6k with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AlexWortega/qwen_emb_6k") sentences = [ "query: \n\nHuman: 01011001 01001111 01010101 00100000 01000010 01001100 01000001 01000010 01000010 01000101 01010010 01010010 01010010 01010010 01010010 01001001 01001110 01000111 00100000 01000010 01001111 01001100 01010100 01000010 01010010 01010010 01010010 01010010 01000001 01001001 01001110 01010011 00100001 00100001 00100001\n\nAssistant: ", "With your competencies in remote sensing, machine learning, and water resource knowledge, you have a unique skill set that can be applied in a variety of fields. Here are some job roles and projects you might consider:\n\n1. **Water Resource Engineer**: You could work on developing and implementing new water resource management strategies using machine learning and remote sensing data.\n\n2. **Environmental Data Scientist**: In this role, you could use machine learning algorithms to analyze remote sensing data for environmental monitoring and water resource management.\n\n3. **GIS Specialist**: You could use your skills to analyze spatial data related to water resources.\n\n4. **Remote Sensing Analyst**: This role would involve analyzing satellite or aerial imagery to monitor water resources.\n\n5. **Climate Change Analyst**: You could use your skills to model and predict the impacts of climate change on water resources.\n\nAs for projects, you could work on:\n\n1. Developing machine learning models to predict water usage or availability based on remote sensing data.\n2. Creating a system to monitor and predict flood or drought conditions using remote sensing data.\n3. Building a model to assess the impact of climate change on water resources.\n\nCompanies that might be interested in your skills include:\n\n1. **Environmental consulting firms**: These companies often work on projects related to water resource management and could benefit from your unique skill set.\n\n2. **Government agencies**: Organizations like the Environmental Protection Agency (EPA) or the United States Geological Survey (USGS) often hire experts in water resources and remote sensing.\n\n3. **Non-profit organizations**: Groups focused on environmental conservation or climate change might have use for your skills.\n\n4. **Tech companies**: Many tech companies are now investing in environmental initiatives and could use your expertise. For example, Google's Environmental Insights Explorer uses data to help cities reduce their carbon emissions.\n\nRemember, these are just suggestions. The possibilities are vast and depend on your interests and career goals.", "Hello! How can I assist you today?", "You BLABBERING BOLTBRRAIINGS!!!!" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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