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---
base_model: unsloth/llama-3-8b-Instruct-bnb-4bit
language:
- en
- vi
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
datasets:
- bkai-foundation-models/vi-self-chat-sharegpt-format
pipeline_tag: text-generation
---
# Llama-8B-Instruct-ShareGPT
- **Developed by:** date3k2
- **License:** apache-2.0
- **Finetuned from model :** unsloth/llama-3-8b-Instruct-bnb-4bit
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/date3k2/unsloth-llama-3-8b-instruct)
## Usage
```python
# !pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
# !pip install --no-deps xformers "trl<0.9.0" peft accelerate bitsandbytes
from unsloth import FastLanguageModel
model, tokenizer = FastLanguageModel.from_pretrained(
model_name = "date3k2/llama3-8b-instruct-sharegpt",
max_seq_length = 2048,
dtype = None,
load_in_4bit = True,
)
FastLanguageModel.for_inference(model) # Enable native 2x faster inference
messages = [
{"from": "human", "value": "Hãy gợi ý một số địa điểm du lịch ở Hà Nội."},
]
inputs = tokenizer.apply_chat_template(
messages,
tokenize = True,
add_generation_prompt = True, # Must add for generation
return_tensors = "pt",
).to("cuda")
from transformers import TextStreamer
text_streamer = TextStreamer(tokenizer)
_ = model.generate(input_ids = inputs, streamer = text_streamer, max_new_tokens = 512, use_cache = True)
``` |