File size: 1,323 Bytes
1e656d5 a963057 1e656d5 a963057 1e656d5 a963057 1e656d5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | readme_content = """---
language:
- en
license: llama3
library_name: transformers
tags:
- nlp
- text-generation
- llama-3
pipeline_tag: text-generation
---
# Llama 3 8B Instruct
This repository contains the weights for the Llama 3 8B Instruct model. It is optimized for chat and instruction-following tasks.
## Model Details
- **Architecture:** Llama 3
- **Size:** 8B Parameters
- **Type:** Instruction Tuned
- **Library:** Transformers
## How to use
You can use this model directly with the Hugging Face `transformers` library:
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
model_id = "maherghanem86/llama3"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto"
)
messages = [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello, how are you?"},
]
input_ids = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
return_tensors="pt"
).to(model.device)
outputs = model.generate(
input_ids,
max_new_tokens=256,
do_sample=True,
temperature=0.6,
top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True)) |