Kushtrim/Phi-3-mini-4k-instruct-sq
Model Overview
The Kushtrim/Phi-3-mini-4k-instruct-sq is a fine-tuned version of the Phi-3-mini-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-mini-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- Information Reliability: Possibility of producing inaccurate or outdated information.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-mini-4k-instruct-sq",
device_map="cuda",
torch_dtype="auto",
trust_remote_code=True,
token=hf_token,
)
tokenizer = AutoTokenizer.from_pretrained("Kushtrim/Phi-3-mini-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.
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for Kushtrim/Phi-3-mini-4k-instruct-sq
Collection including Kushtrim/Phi-3-mini-4k-instruct-sq
Collection
8 items
•
Updated