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MaziyarPanahi / calme-2.1-qwen2-72b
Model's Last Updated: July 25 2024
text-generation
Introduction of calme-2.1-qwen2-72b
Model Details of calme-2.1-qwen2-72b
MaziyarPanahi/calme-2.1-qwen2-72b
This model is a fine-tuned version of the powerful
Qwen/Qwen2-72B-Instruct
, pushing the boundaries of natural language understanding and generation even further. My goal was to create a versatile and robust model that excels across a wide range of benchmarks and real-world applications.
Use Cases
This model is suitable for a wide range of applications, including but not limited to:
- Advanced question-answering systems
- Intelligent chatbots and virtual assistants
- Content generation and summarization
- Code generation and analysis
- Complex problem-solving and decision support
⚡ Quantized GGUF
All GGUF models are available here: MaziyarPanahi/calme-2.1-qwen2-72b-GGUF
🏆 Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 43.61 |
| IFEval (0-Shot) | 81.63 |
| BBH (3-Shot) | 57.33 |
| MATH Lvl 5 (4-Shot) | 36.03 |
| GPQA (0-shot) | 17.45 |
| MuSR (0-shot) | 20.15 |
| MMLU-PRO (5-shot) | 49.05 |
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | |
|---|---|---|---|---|---|---|---|
| truthfulqa_mc2 | 2 | none | 0 | acc | 0.6761 | ± | 0.0148 |
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | |
|---|---|---|---|---|---|---|---|
| winogrande | 1 | none | 5 | acc | 0.8248 | ± | 0.0107 |
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | |
|---|---|---|---|---|---|---|---|
| arc_challenge | 1 | none | 25 | acc | 0.6852 | ± | 0.0136 |
| none | 25 | acc_norm | 0.7184 | ± | 0.0131 |
| Tasks | Version | Filter | n-shot | Metric | Value | Stderr | |
|---|---|---|---|---|---|---|---|
| gsm8k | 3 | strict-match | 5 | exact_match | 0.8582 | ± | 0.0096 |
| flexible-extract | 5 | exact_match | 0.8893 | ± | 0.0086 |
Prompt Template
This model uses
ChatML
prompt template:
<|im_start|>system
{System}
<|im_end|>
<|im_start|>user
{User}
<|im_end|>
<|im_start|>assistant
{Assistant}
How to use
# Use a pipeline as a high-level helper
from transformers import pipeline
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe = pipeline("text-generation", model="MaziyarPanahi/calme-2.1-qwen2-72b")
pipe(messages)
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("MaziyarPanahi/calme-2.1-qwen2-72b")
model = AutoModelForCausalLM.from_pretrained("MaziyarPanahi/calme-2.1-qwen2-72b")
Ethical Considerations
As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments.
Runs of MaziyarPanahi calme-2.1-qwen2-72b on huggingface.co
5.4K
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More Information About calme-2.1-qwen2-72b huggingface.co Model
Url of calme-2.1-qwen2-72b
calme-2.1-qwen2-72b huggingface.co Url
Provider of calme-2.1-qwen2-72b huggingface.co
Other API from MaziyarPanahi
Updated: May 23 2024
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