Text Classification
Transformers
Safetensors
English
Chinese
llama
text-generation
llama3
chinese
function-calling
text-embeddings-inference
Instructions to use ivilson/llama3-8b-chinese-function-calling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivilson/llama3-8b-chinese-function-calling with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ivilson/llama3-8b-chinese-function-calling")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ivilson/llama3-8b-chinese-function-calling") model = AutoModelForCausalLM.from_pretrained("ivilson/llama3-8b-chinese-function-calling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00002-of-00017.safetensors from ivilson/llama3-8b-chinese-function-calling: direct link, hf CLI and curl.
- Browser
- Download file 956 MB
-
https://huggingface.co/ivilson/llama3-8b-chinese-function-calling/resolve/main/model-00002-of-00017.safetensors
- Command line
-
hf download hf://ivilson/llama3-8b-chinese-function-calling/model-00002-of-00017.safetensors
-
curl -L -o model-00002-of-00017.safetensors https://huggingface.co/ivilson/llama3-8b-chinese-function-calling/resolve/main/model-00002-of-00017.safetensors
956 MB
- Xet hash:
- 090729e79ebce83443fe2209a92a5cecba7f248c9b2abed56546f4978e6370fe
- Size of remote file:
- 956 MB
- SHA256:
- 809959697a6ec929da1355ffa3620bffe5c2cfa2de2506131b507221c81f0d6f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.