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L3_financial_news_headlines_Word2Vec
firobeid/L3_financial_news_headlines_Word2Vec
L3_financial_news_headlines_Word2Vec is a machine learning model from firobeid. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
This model contains custom word embeddings trained using Gensim's Word2Vec implementation.
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.tsv262 MB · 74%
At a glance
- License
- mit
- Model type
- word2vec
- Access
- Public
- Created
- May 14, 2025
- Updated
- May 14, 2025
- SHA
- 279772e4
Datasets
Model card
From the Hugging Face model README
Custom Word2Vec Embeddings
This model contains custom word embeddings trained using Gensim's Word2Vec implementation.
Model details
- Trained using Gensim's Word2Vec
- Includes custom n-grams as tokens
- Vector size: 100
- Context window: 5
- Training algorithm: Skip-gram
Usage
from transformers import AutoTokenizer, AutoModel
import torch
# Load model directly
from transformers import AutoModel, AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("your-username/your-model-name")
model = AutoModel.from_pretrained("your-username/your-model-name")
# Or load from the hub using gensim:
from gensim.models import KeyedVectors
import gensim.downloader as api
# Load vectors directly using gensim
word_vectors = api.load("your-username/your-model-name")
- Type
- word2vec
- License
- mit
- Languages
- en
- Created
- May 14, 2025
- Updated
- May 14, 2025