Kushtrim/Phi-3-medium-4k-instruct-sq
Model Overview
The Kushtrim/Phi-3-medium-4k-instruct-sq is a fine-tuned version of the Phi-3-Medium-4K-Instruct model, specifically tailored for Albanian language tasks. It has a context length of up to 4,000 tokens, making it suitable for a variety of applications requiring strong reasoning and high-quality outputs in Albanian.
Model Details
- Model Name: Kushtrim/Phi-3-medium-4k-instruct-sq
- Base Model: Phi-3-Mini-4K-Instruct
- Context Length: 4,000 tokens
- Language: Albanian
- License: MIT License
Limitations
- Representation of Harms & Stereotypes: Potential for biased outputs reflecting real-world societal biases.
- Inappropriate or Offensive Content: Risk of generating content that may be offensive or inappropriate in certain contexts.
- Information Reliability: Possibility of producing inaccurate or outdated information.
- Dataset Size: The Albanian dataset used for fine-tuning was not very large, which may affect the model's performance and coverage.
Responsible AI Considerations
Developers using this model should:
- Evaluate and mitigate risks related to accuracy, safety, and fairness.
- Ensure compliance with applicable laws and regulations.
- Implement additional safeguards for high-risk scenarios and sensitive contexts.
- Inform end-users that they are interacting with an AI system.
- Use feedback mechanisms and contextual information grounding techniques (RAG) to enhance output reliability.
How to Use
!pip3 install -U transformers peft accelerate bitsandbytes
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
import torch
hf_token = "hf_...." #
torch.random.manual_seed(0)
model = AutoModelForCausalLM.from_pretrained(
"Kushtrim/Phi-3-medium-4k-instruct-sq",
device_map="cuda",
torch_dtype="auto",
trust_remote_code=True,
token=hf_token,
)
tokenizer = AutoTokenizer.from_pretrained("Kushtrim/Phi-3-medium-4k-instruct-sq", token=hf_token)
messages = [
{"role": "system", "content": "Je një asistent inteligjent shumë i dobishëm."},
{"role": "user", "content": "Identifiko emrat e personave në këtë artikull 'Majlinda Kelmendi (lindi më 9 maj 1991), është një xhudiste shqiptare nga Peja, Kosovë.'"},
]
pipe = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
)
generation_args = {
"max_new_tokens": 1024,
"return_full_text": False,
"temperature": 0.7,
"do_sample": True,
}
output = pipe(messages, **generation_args)
print(output[0]['generated_text'])
Acknowledgements
This model is built upon the Phi-3-Mini-4K-Instruct by leveraging its robust capabilities and further fine-tuning it for Albanian language tasks. Special thanks to the developers and researchers who contributed to the original Phi-3 models.
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