Summarization
Transformers
PyTorch
English
llama
text-generation
unsloth
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use NiCEtmtm/llama3_torch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NiCEtmtm/llama3_torch 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="NiCEtmtm/llama3_torch")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NiCEtmtm/llama3_torch") model = AutoModelForCausalLM.from_pretrained("NiCEtmtm/llama3_torch", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from NiCEtmtm/llama3_torch: direct link, hf CLI and curl.
- Browser
- Download file 9.09 MB
-
https://huggingface.co/NiCEtmtm/llama3_torch/resolve/main/tokenizer.json
- Command line
-
hf download hf://NiCEtmtm/llama3_torch/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/NiCEtmtm/llama3_torch/resolve/main/tokenizer.json
9.09 MB
File too large to display, you can check the raw version instead.