Text Generation
Transformers
Safetensors
llama
Merge
mergekit
lazymergekit
dhanushreddy29/BrokenKeyboard
udkai/Turdus
conversational
Eval Results (legacy)
text-generation-inference
Instructions to use dhanushreddy29/BrokenKeyboardMerge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhanushreddy29/BrokenKeyboardMerge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dhanushreddy29/BrokenKeyboardMerge") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("dhanushreddy29/BrokenKeyboardMerge") model = AutoModelForCausalLM.from_pretrained("dhanushreddy29/BrokenKeyboardMerge") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use dhanushreddy29/BrokenKeyboardMerge with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dhanushreddy29/BrokenKeyboardMerge" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dhanushreddy29/BrokenKeyboardMerge", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/dhanushreddy29/BrokenKeyboardMerge
- SGLang
How to use dhanushreddy29/BrokenKeyboardMerge with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "dhanushreddy29/BrokenKeyboardMerge" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dhanushreddy29/BrokenKeyboardMerge", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "dhanushreddy29/BrokenKeyboardMerge" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dhanushreddy29/BrokenKeyboardMerge", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use dhanushreddy29/BrokenKeyboardMerge with Docker Model Runner:
docker model run hf.co/dhanushreddy29/BrokenKeyboardMerge
Adding Evaluation Results
#2
by leaderboard-pr-bot - opened
README.md
CHANGED
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@@ -9,6 +9,109 @@ tags:
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base_model:
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- dhanushreddy29/BrokenKeyboard
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- udkai/Turdus
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---
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# BrokenKeyboardMerge
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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-
```
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base_model:
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- dhanushreddy29/BrokenKeyboard
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- udkai/Turdus
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+
model-index:
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+
- name: BrokenKeyboardMerge
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+
results:
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+
- task:
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+
type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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+
value: 59.73
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name: normalized accuracy
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| 29 |
+
source:
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| 30 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboardMerge
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name: Open LLM Leaderboard
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+
- task:
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+
type: text-generation
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| 34 |
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name: Text Generation
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| 35 |
+
dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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+
metrics:
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- type: acc_norm
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value: 81.25
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name: normalized accuracy
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+
source:
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| 46 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboardMerge
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name: Open LLM Leaderboard
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| 48 |
+
- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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+
metrics:
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- type: acc
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| 60 |
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value: 58.36
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| 61 |
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name: accuracy
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| 62 |
+
source:
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| 63 |
+
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboardMerge
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name: Open LLM Leaderboard
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- task:
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| 66 |
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type: text-generation
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| 67 |
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 52.0
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| 78 |
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source:
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| 79 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboardMerge
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| 80 |
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name: Open LLM Leaderboard
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| 81 |
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- task:
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| 82 |
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type: text-generation
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| 83 |
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name: Text Generation
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| 84 |
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dataset:
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| 85 |
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name: Winogrande (5-shot)
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| 86 |
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type: winogrande
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| 87 |
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config: winogrande_xl
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| 88 |
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 78.69
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| 94 |
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name: accuracy
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source:
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| 96 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboardMerge
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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| 110 |
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value: 25.93
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| 111 |
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name: accuracy
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| 112 |
+
source:
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| 113 |
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=dhanushreddy29/BrokenKeyboardMerge
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| 114 |
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name: Open LLM Leaderboard
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| 115 |
---
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# BrokenKeyboardMerge
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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+
```
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+
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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| 162 |
+
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_dhanushreddy29__BrokenKeyboardMerge)
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| 163 |
+
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| 164 |
+
| Metric |Value|
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| 165 |
+
|---------------------------------|----:|
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| 166 |
+
|Avg. |59.33|
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| 167 |
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|AI2 Reasoning Challenge (25-Shot)|59.73|
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| 168 |
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|HellaSwag (10-Shot) |81.25|
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| 169 |
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|MMLU (5-Shot) |58.36|
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| 170 |
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|TruthfulQA (0-shot) |52.00|
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| 171 |
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|Winogrande (5-shot) |78.69|
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| 172 |
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|GSM8k (5-shot) |25.93|
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| 173 |
+
|