Instructions to use Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7 with Transformers:

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

pipe = pipeline("text-generation", model="Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7")
model = AutoModelForCausalLM.from_pretrained("Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7

SGLang

How to use Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7 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 "Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7 with Docker Model Runner:
```
docker model run hf.co/Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7
```

Sefika commited on Sep 13, 2025

Commit

1ffe40f

verified ·

1 Parent(s): 29d77a1

Upload Qwen2ForCausalLM

Browse files

Files changed (4) hide show

config.json +32 -3
generation_config.json +1 -2
model-00001-of-00002.safetensors +1 -1
model.safetensors.index.json +1 -0

config.json CHANGED Viewed

@@ -1,14 +1,44 @@
 {
-  "_name_or_path": "Sefika/CRE_fewrel_qwen_10_3_task_memory_10_7",
   "architectures": [
     "Qwen2ForCausalLM"
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   "max_window_layers": 28,
   "model_type": "qwen2",
@@ -37,8 +67,7 @@
   "rope_theta": 1000000.0,
   "sliding_window": null,
   "tie_word_embeddings": false,
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-  "transformers_version": "4.45.2",
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   "use_sliding_window": false,
   "vocab_size": 152064

 {
   "architectures": [
     "Qwen2ForCausalLM"
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   "eos_token_id": 151645,
   "hidden_act": "silu",
   "hidden_size": 3584,
   "initializer_range": 0.02,
   "intermediate_size": 18944,
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   "model_type": "qwen2",
   "rope_theta": 1000000.0,
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   "tie_word_embeddings": false,
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generation_config.json CHANGED Viewed

@@ -1,5 +1,4 @@
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   "do_sample": true,
   "eos_token_id": [
     151645,
@@ -10,5 +9,5 @@
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-  "transformers_version": "4.45.2"
 }

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   "eos_token_id": [
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   "temperature": 0.7,
   "top_k": 20,
   "top_p": 0.8,
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 }

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