Question Answering
Transformers
Safetensors
llama
text-generation
smollm2
automotive
instruction-tuning
domain-adaptation
workshop-assistant
text-generation-inference
Instructions to use ShaileshH/smol-workertech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ShaileshH/smol-workertech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="ShaileshH/smol-workertech")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ShaileshH/smol-workertech") model = AutoModelForCausalLM.from_pretrained("ShaileshH/smol-workertech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcf2903fc2f3cc71d1b63169c9cab5ebee459c694fe70295e267d76a7188a07d
- Size of remote file:
- 269 MB
- SHA256:
- a4c5dab602e7035d745b66a7031c1d02f5de3241abdff354386ae9a46cc23dbd
路
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