Model Card for Model ID
Hungarian Astronomy Question-Answering mamba modell SFT-training epoch 1.
Model Details
Model Description
This is an experimental mamba-130m-hf Small LM tuned to RAG for amateur astronomy. (Answer based on the context provided.)
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: [Gábor Madarász]
- Funded by [optional]: [Kaggle]
- Shared by [optional]: [More Information Needed]
- Model type: [Mamba]
- Language(s) (NLP): [More Information Needed]
- License: [More Information Needed]
- Finetuned from model [optional]: [More Information Needed]
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How to Get Started with the Model
Use the code below to get started with the model.
1from transformers import pipeline
2
3# Load the model
4
5model_name = "GaborMadarasz/AstroQA_mamba_V10" #"/home/gabor/Dokumentumok/Munka/hobby/mamba/AstroQA_mamba/checkpoint30"
6
7# Initialize the text generation pipeline
8generator = pipeline("text-generation", model=model_name)
9
10question = "Mikor sikerült újra észlelni az üstököst?" # "Milyen fényes volt az üstkökös?" #"Mikor sikerült újra észlelni az üstököst?"
11
12context = """Az általam 6,5 magnitúdósra becsült üstö-
13kös ugyan messze volt már az M3-tól, de
14a kompakt kóma és a több mint egy fok
15hosszú csóva látványa valamelyest kárpó-
16tolt minket. Néhány nappal később, decem-
17ber 7-én sokaknak sikerült újra észlelni
18az üstököst, én is megpróbálkoztam, bár
19Budapestről már annak is örültem, hogy
20a Corona Borealis csillagait sikerült bino-
21kulárral megtalálnom. """
22
23prompt = f"Query:\n{question}\n\n### Input:\n{context}\n\n### Response:\n"
24
25
26# Generate text with recommended parameters
27output = generator(
28 prompt, # Example prompt in Hungarian
29 max_new_tokens=256,
30 do_sample=True,
31 repetition_penalty=1.35,
32 temperature=0.1,
33 top_k=120,
34 top_p=0.98,
35 truncation=True,
36 return_full_text=False,
37
38)
39
40# Print the generated text
41print(output[0]["generated_text"])
42
Training Details
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Environmental Impact
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
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