--- library_name: transformers tags: [] --- # Model Card for Model ID ## Model Details ### Model Description This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - **Developed by:** drimeF0 - **Model type:** Gemma3TextForSequenceClassification - **Language(s) (NLP):** en - **Finetuned from model:** https://huggingface.co/google/gemma-3-270m ### Direct Use ```py id2label = {0: "NEGATIVE", 1: "POSITIVE"} label2id = {"NEGATIVE": 0, "POSITIVE": 1} tokenizer = AutoTokenizer.from_pretrained("femboysLover/gemini_trader_embeddings") model = AutoModelForSequenceClassification.from_pretrained( "femboysLover/gemini_trader_embeddings", num_labels=2, id2label=id2label, label2id=label2id ) text = """ returns:0.002405 price_above_moving_fast: true recent_news: Date: 2023-06-26 14:56:49 Title: Bitcoin markets are staying resilient! Despite low market liquidity and volatility, HODLers continue to accumulate… Date: 2023-06-26 16:32:17 Title: Bitcoin Could Soar 10X To Hit $300,000, Reckons XRP Holders’ Lawyer — Here’s How Date: 2023-06-27 03:00:59 Title: Jump Trading Accumulating DeFi Tokens, Including LDO, PERP, and MASK Date: 2023-06-27 09:30:06 Title: Bitcoin Cash climbs 100% in a week adding over $2 billion to market cap (up to 48 news) """ classifier = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer) print(classifier(text)) # [{'label': 'POSITIVE', 'score': 0.6116430163383484}] # good entry point for long ``` ## Training Details ### Training Data https://github.com/soheilrahsaz/cryptoNewsDataset