Quantizations of https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct
Note: Quantized using version b3482 of llama.cpp, which should resolve the rope scaling issue. You will need the latest llama.cpp to use these quants.
Inference Clients/UIs
From original readme
Use with transformers
Starting with transformers >= 4.43.0
onward, you can run conversational inference using the Transformers pipeline
abstraction or by leveraging the Auto classes with the generate()
function.
Make sure to update your transformers installation via pip install --upgrade transformers
.
import transformers
import torch
model_id = "meta-llama/Meta-Llama-3.1-8B-Instruct"
pipeline = transformers.pipeline(
"text-generation",
model=model_id,
model_kwargs={"torch_dtype": torch.bfloat16},
device_map="auto",
)
messages = [
{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
{"role": "user", "content": "Who are you?"},
]
outputs = pipeline(
messages,
max_new_tokens=256,
)
print(outputs[0]["generated_text"][-1])
Note: You can also find detailed recipes on how to use the model locally, with torch.compile()
, assisted generations, quantised and more at huggingface-llama-recipes
Use with llama
Please, follow the instructions in the repository
To download Original checkpoints, see the example command below leveraging huggingface-cli
:
huggingface-cli download meta-llama/Meta-Llama-3.1-8B-Instruct --include "original/*" --local-dir Meta-Llama-3.1-8B-Instruct
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