Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

johnnas12
/
e5-galaxy-finetuned

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:68840
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use johnnas12/e5-galaxy-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use johnnas12/e5-galaxy-finetuned with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("johnnas12/e5-galaxy-finetuned")
    
    sentences = [
        "query: How can I hicmergeloops?",
        "passage: WindowMasker mkcounts. Construct WindowMasker unit counts table. **What it does**  This tool runs `stage 1 <https://www.ncbi.nlm.nih.gov/IEB/ToolBox/CPP_DOC/lxr/source/src/app/winmasker/>`_ of the WindowMasker analysis to produce a unit counts file for a genome assembly.",
        "passage: GROMACS simulation. for system equilibration or data collection. .. class:: infomark  **What it does**  This tool performs a molecular dynamics simulation with GROMACS.  _____  .. class:: infomark  **Input**         - GRO structure file.        - Topology (TOP) file.  A variety of other options can also be specified:        - MDP parameter file to take advantage of all GROMACS features. Otherwise, choose parameters through the Galaxy interface. See the `manual`_ for more information on the options.        - Accepting and producing checkpoint (CPT) input/output files, which allows sequential MD simulations, e.g. when performing NVT and NPT equilibration followed by a production simulation.        - Position restraint (ITP) file, useful for equilibrating solvent around a protein.        - Choice of ensemble: NVT or NPT.        - Whether to return trajectory (XTC or TRR) and/or structure (GRO or PDB) files.  .. _`manual`: http://manual.gromacs.org/documentation/2018/user-guide/mdp-options.html  _____           .. class:: infomark  **Output**         - Structure and/or trajectory files as specified in the input.",
        "passage: hicMergeLoops. merge detected loops of different resolutions.. Merge detected loops ====================  This script merges the loop locations of different different resolutions.  Loops need to have the following format:  chr start end chr start end  A merge happens if x and y position of a loop overlaps with x and y position of another loop; all loops are considered as an overlap within +/- the bin size of the lowest resolution. I.e. for a loop with coordinates x and y, the overlap to all other loops is searched for (x - lowest resolution) and (y + lowest resolution). If two or more locations should be merged, the one with the lowest resolution is taken as the merged loop.  Example usage:  `$ hicMergeLoops -i gm12878_10kb.bedgraph gm12878_5kb.bedgraph gm12878_25kb.bedgraph -o merged_result.bedgraph -r 25000`  Please recall: We work with binned data i.e. the lowest resolution is therefore the one where we merge the most bases into one bin. In the above example the lowest resultion is 25kb, the highest resolution is 5kb.   For more information about HiCExplorer please consider our documentation on readthedocs.io_  .. _readthedocs.io: http://hicexplorer.readthedocs.io/en/latest/index.html"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
e5-galaxy-finetuned
439 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 15 commits
johnnas12's picture
johnnas12
Upload 1_Pooling/config.json
7df40e3 verified 8 months ago
  • 1_Pooling
    Upload 1_Pooling/config.json 8 months ago
  • .gitattributes
    1.52 kB
    initial commit 8 months ago
  • README.md
    42.5 kB
    Upload README.md 8 months ago
  • config.json
    954 Bytes
    Upload config.json 8 months ago
  • config_sentence_transformers.json
    205 Bytes
    Upload config_sentence_transformers.json 8 months ago
  • model.safetensors
    438 MB
    xet
    Upload fine-tuned E5 model 8 months ago
  • modules.json
    349 Bytes
    Upload modules.json 8 months ago
  • sentence_bert_config.json
    53 Bytes
    Upload sentence_bert_config.json 8 months ago
  • special_tokens_map.json
    695 Bytes
    Upload special_tokens_map.json 8 months ago
  • tokenizer.json
    712 kB
    Upload tokenizer.json 8 months ago
  • tokenizer_config.json
    1.22 kB
    Upload tokenizer_config.json 8 months ago
  • vocab.txt
    232 kB
    Upload vocab.txt 8 months ago