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---
language:
- en
license: mit
tags:
- nlp
- code
- mlx
datasets:
- teknium/openhermes
license_link: https://huggingface.co/microsoft/phi-2/resolve/main/LICENSE
pipeline_tag: text-generation
model-index:
- name: phi-2-openhermes-30k
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 61.01
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=marcel/phi-2-openhermes-30k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 74.72
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=marcel/phi-2-openhermes-30k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 57.17
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=marcel/phi-2-openhermes-30k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 45.38
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=marcel/phi-2-openhermes-30k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 74.9
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=marcel/phi-2-openhermes-30k
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 49.05
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=marcel/phi-2-openhermes-30k
name: Open LLM Leaderboard
---
# marcel/phi-2-openhermes-30k
This model was converted to MLX format from [`microsoft/phi-2`]().
Refer to the [original model card](https://huggingface.co/microsoft/phi-2) for more details on the model.
## Use with mlx
```bash
pip install mlx
git clone https://github.com/ml-explore/mlx-examples.git
cd mlx-examples/llms/hf_llm
python generate.py --model marcel/phi-2-openhermes-30k --prompt "My name is"
```
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"marcel/phi-2-openhermes-30k",
low_cpu_mem_usage=True,
device_map="auto",
trust_remote_code=True,
torch_dtype=torch.float16,
)
tokenizer = AutoTokenizer.from_pretrained("phi-2-openhermes-30k")
input_text = "### Human: Give me a good recipe for a chinese dish\n\n### Assistant:"
outputs = model.generate(
tokenizer(input_text, return_tensors="pt").to(model.device)['input_ids'],
max_length=1024,
temperature=0.7,
top_p=0.9,
do_sample=True,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id,
)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_marcel__phi-2-openhermes-30k)
| Metric |Value|
|---------------------------------|----:|
|Avg. |60.37|
|AI2 Reasoning Challenge (25-Shot)|61.01|
|HellaSwag (10-Shot) |74.72|
|MMLU (5-Shot) |57.17|
|TruthfulQA (0-shot) |45.38|
|Winogrande (5-shot) |74.90|
|GSM8k (5-shot) |49.05|
|