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Model Description:
This model is fine-tuned on text scraped from 100+ Mechanical/Automotive pdf books.
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Model Type: Causal Language modeling
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Language(s): English
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License: [More Information Needed]
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Parent Model: See the
DistilGPT2model for more information about the Distilled-GPT2 base model.
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Resources for more information:
The model can be used for tasks including topic classification, Causal Language modeling and text generation
The model should not be used to intentionally create hostile or alienating environments for people. In addition, the model was not trained to be factual or true representations of people or events, and therefore using the model to generate such content is out-of-scope for the abilities of this model.
Significant research has explored bias and fairness issues with language models (see, e.g.,
Sheng et al. (2021) and
Bender et al. (2021)).
This model is fine-tuned on text scraped from 100+ Mechanical/Automotive pdf books.
Carbon emissions can be estimated using the
Machine Learning Impact calculator presented in
Lacoste et al. (2019).
1from transformers import AutoTokenizer, AutoModelForCausalLM
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3tokenizer = AutoTokenizer.from_pretrained("geralt/MechDistilGPT2")
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5model = AutoModelForCausalLM.from_pretrained("geralt/MechDistilGPT2")
6
