Instructions to use HumanLLMs/Human-Like-Qwen2.5-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HumanLLMs/Human-Like-Qwen2.5-7B-Instruct with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="HumanLLMs/Human-Like-Qwen2.5-7B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("HumanLLMs/Human-Like-Qwen2.5-7B-Instruct")
model = AutoModelForCausalLM.from_pretrained("HumanLLMs/Human-Like-Qwen2.5-7B-Instruct", device_map="auto")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use HumanLLMs/Human-Like-Qwen2.5-7B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "HumanLLMs/Human-Like-Qwen2.5-7B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "HumanLLMs/Human-Like-Qwen2.5-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/HumanLLMs/Human-Like-Qwen2.5-7B-Instruct

SGLang

How to use HumanLLMs/Human-Like-Qwen2.5-7B-Instruct 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 "HumanLLMs/Human-Like-Qwen2.5-7B-Instruct" \
    --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": "HumanLLMs/Human-Like-Qwen2.5-7B-Instruct",
		"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 "HumanLLMs/Human-Like-Qwen2.5-7B-Instruct" \
        --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": "HumanLLMs/Human-Like-Qwen2.5-7B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use HumanLLMs/Human-Like-Qwen2.5-7B-Instruct with Docker Model Runner:
```
docker model run hf.co/HumanLLMs/Human-Like-Qwen2.5-7B-Instruct
```

Weyaxi commited on Jan 10, 2025

Commit

0e4c303

verified ·

1 Parent(s): b93a89b

readme minor change

Browse files

Files changed (1) hide show

README.md +18 -9

README.md CHANGED Viewed

@@ -4,7 +4,6 @@ tags:
 - axolotl
 - dpo
 - trl
-- generated_from_trainer
 base_model: Qwen/Qwen2.5-7B-Instruct
 model-index:
 - name: Humanish-Qwen2.5-7B-Instruct
@@ -22,7 +21,8 @@ model-index:
       value: 72.84
       name: strict accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -37,7 +37,8 @@ model-index:
       value: 34.48
       name: normalized accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -49,10 +50,11 @@ model-index:
         num_few_shot: 4
     metrics:
     - type: exact_match
-      value: 0.0
       name: exact match
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -67,7 +69,8 @@ model-index:
       value: 6.49
       name: acc_norm
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -82,7 +85,8 @@ model-index:
       value: 8.42
       name: acc_norm
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -99,8 +103,13 @@ model-index:
       value: 37.76
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
 ---
 <div align="center">
   <img src="https://cdn-avatars.huggingface.co/v1/production/uploads/63da3d7ae697e5898cb86854/H-vpXOX6KZu01HnV87Jk5.jpeg" width="320" height="320" />
@@ -287,4 +296,4 @@ More details on the dataset creation process can be found in the accompanying re
       primaryClass={cs.CL},
       url={https://arxiv.org/abs/2501.05032},
 }
-```

 - axolotl
 - dpo
 - trl
 base_model: Qwen/Qwen2.5-7B-Instruct
 model-index:
 - name: Humanish-Qwen2.5-7B-Instruct
       value: 72.84
       name: strict accuracy
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 34.48
       name: normalized accuracy
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
         num_few_shot: 4
     metrics:
     - type: exact_match
+      value: 0
       name: exact match
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 6.49
       name: acc_norm
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 8.42
       name: acc_norm
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
   - task:
       type: text-generation
       value: 37.76
       name: accuracy
     source:
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=HumanLLMs/Humanish-Qwen2.5-7B-Instruct
       name: Open LLM Leaderboard
+datasets:
+- HumanLLMs/Human-Like-DPO-Dataset
+language:
+- en
 ---
 <div align="center">
   <img src="https://cdn-avatars.huggingface.co/v1/production/uploads/63da3d7ae697e5898cb86854/H-vpXOX6KZu01HnV87Jk5.jpeg" width="320" height="320" />
       primaryClass={cs.CL},
       url={https://arxiv.org/abs/2501.05032},
 }
+```