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abanfalvi
/
finance-llama-nemotron-embed-1b-v2

Sentence Similarity
sentence-transformers
Safetensors
llama_bidirec
feature-extraction
Generated from Trainer
dataset_size:15509
loss:MultipleNegativesRankingLoss
custom_code
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use abanfalvi/finance-llama-nemotron-embed-1b-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use abanfalvi/finance-llama-nemotron-embed-1b-v2 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("abanfalvi/finance-llama-nemotron-embed-1b-v2", trust_remote_code=True)
    
    sentences = [
        "What was the total underlying EBITDA for FY23?",
        "Refining & Chemicals\n\nRefining Chemicals Q1 2020 -6,292 -2,410 Q1 2021 10,205 4,470 Change Q1 2020 to Q1 2021 +16,497 +6,880\n\n'000 tons\n\nQ1 2020 Q1 2021 Volume 276.5 298.0 Change +7.8%\n\nOperating Profit\n\nProduction of Major Chemical Products\n\nRMB Million\n\n'000 tons\n\nCrude Processing Volume\n\nProduction of Major Oil Products\n\nMM bbl\n\nQ1 2021 Q1 2020 Change Ethylene 1,609 1,539 4.5% Synthetic Resin 2,642 2,473 6.8% Synthetic Fiber Raw Materials 316 342 -7.6% Synthetic Rubber 263 246 6.9% Urea 382 261 46.4%\n\nQ1 2021 Q1 2020 Change Total 26,946 25,208 6.9% Gasoline 12,395 10,967 13.0% Kerosene 2,842 2,394 18.7% Diesel 11,709 11,847 -1.2%",
        "Year Core business TCXO chip shortage Total FY19 $114m $114m FY20 $119m $119m FY21 $128m $128m FY22 $141m $8m $149m FY23 $164m $8m $172m\n\nStrong core business growth offsets chip-shortage revenue impacts Financial result reflects investment in future growth and inflationary pressures\n\nRevenue\n\nRevenue Gross Margin $180.3m $88.8m ▲$8.4m +5% ▼$1.3m -7%\n\nUnderlying EBITDA Operating cash flow $42.2m $11.1m ▼$12.2m -23% ▼$19.1m -63%\n\nNet profit after tax Net cash $23.2m $16.5m ▼$-9.9m -30% ▼$6.8m -29%\n\nYear Core TCXO chip shortage Associate Total FY19 $11m $11m FY20 $15m $15m FY21 $23m $23m FY22 $37m $11m $15m $63m FY23 $39m $11m $15m $65m\n\nUnderlying EBITDA",
        "Key Metrics Significant growth across all key metrics\n\nFY23 includes an 8-month contribution from StarVale (completed 1 November 2022).\n\nOperating cash flow less capex.\n\nNPATA and EPSA are before amortisation of acquired intangible assets.\n\nMetric FY24 ($m) FY23 ($m) Growth (%) Notes Total Transaction Value 1,054 852 +24% Lottery Retailing 544 (FY23: 449) Group Revenue 159.3 118.7 +34% Revenue Margin 15.1% (FY23: 13.9%) Underlying EBITDA 2 76.6 58.9 +30% Und. EBITDA Margin 48.1% (FY23: 49.6%) Underlying NPATA 2,3 46.4 35.3 +31% Und. EPSA 2,3 73.7 cps (FY23: 56.1 cps) Free Cash Flow 4 54.1 47.5 +14% Cash Conversion 125% (FY23: 146%) Dividend Declared (cps) 54.5 43.0 +27% 1H: 27.0 cps (23.0)\n\nUnderlying reflects adjustments for one-off costs: EBITDA $1.4m in FY24 (FY23: $0.8m) and NPATA $0.8m in FY24 (FY23: $1.5m)."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
finance-llama-nemotron-embed-1b-v2
2.53 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
abanfalvi's picture
abanfalvi
Add new SentenceTransformer model
b75bb25 verified 11 days ago
  • 1_Pooling
    Add new SentenceTransformer model 11 days ago
  • .gitattributes
    1.57 kB
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  • README.md
    67.3 kB
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  • config.json
    1.12 kB
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  • config_sentence_transformers.json
    299 Bytes
    Add new SentenceTransformer model 11 days ago
  • llama_bidirectional_model.py
    9.06 kB
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  • model.safetensors
    2.52 GB
    xet
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  • modules.json
    429 Bytes
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  • sentence_bert_config.json
    241 Bytes
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  • tokenizer.json
    17.2 MB
    xet
    Add new SentenceTransformer model 11 days ago
  • tokenizer_config.json
    333 Bytes
    Add new SentenceTransformer model 11 days ago