Summarization
Transformers
Safetensors
Malayalam
llama
text-generation
malayalam
dapt
text-generation-inference
Instructions to use Navneeth017/sarvam1-dapt-general with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Navneeth017/sarvam1-dapt-general with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="Navneeth017/sarvam1-dapt-general")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Navneeth017/sarvam1-dapt-general") model = AutoModelForCausalLM.from_pretrained("Navneeth017/sarvam1-dapt-general", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Navneeth017/sarvam1-dapt-general: direct link, hf CLI and curl.
- Browser
- Download file 8.51 MB
-
https://huggingface.co/Navneeth017/sarvam1-dapt-general/resolve/main/tokenizer.json
- Command line
-
hf download hf://Navneeth017/sarvam1-dapt-general/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Navneeth017/sarvam1-dapt-general/resolve/main/tokenizer.json
8.51 MB
File too large to display, you can check the raw version instead.