Instructions to use AIencoder/Qwen2.5CMR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AIencoder/Qwen2.5CMR with Transformers:

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

pipe = pipeline("text-generation", model="AIencoder/Qwen2.5CMR")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AIencoder/Qwen2.5CMR")
model = AutoModelForCausalLM.from_pretrained("AIencoder/Qwen2.5CMR")
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 AIencoder/Qwen2.5CMR with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/AIencoder/Qwen2.5CMR

SGLang

How to use AIencoder/Qwen2.5CMR 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 "AIencoder/Qwen2.5CMR" \
    --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": "AIencoder/Qwen2.5CMR",
		"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 "AIencoder/Qwen2.5CMR" \
        --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": "AIencoder/Qwen2.5CMR",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AIencoder/Qwen2.5CMR with Docker Model Runner:
```
docker model run hf.co/AIencoder/Qwen2.5CMR
```

AIencoder commited on Feb 8

Commit

86155a9

verified ·

1 Parent(s): 85f68d3

Upload folder using huggingface_hub

Browse files

Files changed (8) hide show

README.md +16 -16
config.json +2 -2
mergekit_config.yml +15 -14
model-00001-of-00004.safetensors +1 -1
model-00002-of-00004.safetensors +1 -1
model-00003-of-00004.safetensors +1 -1
model-00004-of-00004.safetensors +1 -1
tokenizer_config.json +1 -1

README.md CHANGED Viewed

@@ -2,7 +2,6 @@
 base_model:
 - Qwen/Qwen2.5-Coder-7B-Instruct
 - Qwen/Qwen2.5-Math-7B-Instruct
-- Qwen/Qwen2.5-7B-Instruct
 library_name: transformers
 tags:
 - mergekit
@@ -16,7 +15,7 @@ This is a merge of pre-trained language models created using [mergekit](https://
 ## Merge Details
 ### Merge Method
-This model was merged using the [DARE TIES](https://arxiv.org/abs/2311.03099) merge method using [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) as a base.
 ### Models Merged
@@ -30,21 +29,22 @@ The following YAML configuration was used to produce this model:
 ```yaml
-models:
-  - model: Qwen/Qwen2.5-Coder-7B-Instruct
-    parameters:
-      weight: 0.5
-      density: 0.7
-  - model: Qwen/Qwen2.5-Math-7B-Instruct
-    parameters:
-      weight: 0.5
-      density: 0.6
-merge_method: dare_ties
-base_model: Qwen/Qwen2.5-7B-Instruct
 parameters:
-  int8_mask: true
-  normalize: true
 dtype: bfloat16
-tokenizer_source: Qwen/Qwen2.5-7B-Instruct
 ```

 base_model:
 - Qwen/Qwen2.5-Coder-7B-Instruct
 - Qwen/Qwen2.5-Math-7B-Instruct
 library_name: transformers
 tags:
 - mergekit
 ## Merge Details
 ### Merge Method
+This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
 ### Models Merged
 ```yaml
+slices:
+  - sources:
+      - model: Qwen/Qwen2.5-Coder-7B-Instruct
+        layer_range: [0, 28]
+      - model: Qwen/Qwen2.5-Math-7B-Instruct
+        layer_range: [0, 28]
+merge_method: slerp
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
 parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
 dtype: bfloat16
+tokenizer_source: Qwen/Qwen2.5-Coder-7B-Instruct
 ```

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
   "architectures": [
     "Qwen2ForCausalLM"
   ],
@@ -22,7 +22,7 @@
   "sliding_window": null,
   "tie_word_embeddings": false,
   "torch_dtype": "bfloat16",
-  "transformers_version": "4.46.0",
   "use_cache": true,
   "use_sliding_window": false,
   "vocab_size": 151665

 {
+  "_name_or_path": "Qwen/Qwen2.5-Coder-7B-Instruct",
   "architectures": [
     "Qwen2ForCausalLM"
   ],
   "sliding_window": null,
   "tie_word_embeddings": false,
   "torch_dtype": "bfloat16",
+  "transformers_version": "4.46.3",
   "use_cache": true,
   "use_sliding_window": false,
   "vocab_size": 151665

mergekit_config.yml CHANGED Viewed

@@ -1,17 +1,18 @@
-models:
-  - model: Qwen/Qwen2.5-Coder-7B-Instruct
-    parameters:
-      weight: 0.5
-      density: 0.7
-  - model: Qwen/Qwen2.5-Math-7B-Instruct
-    parameters:
-      weight: 0.5
-      density: 0.6
-merge_method: dare_ties
-base_model: Qwen/Qwen2.5-7B-Instruct
 parameters:
-  int8_mask: true
-  normalize: true
 dtype: bfloat16
-tokenizer_source: Qwen/Qwen2.5-7B-Instruct

+slices:
+  - sources:
+      - model: Qwen/Qwen2.5-Coder-7B-Instruct
+        layer_range: [0, 28]
+      - model: Qwen/Qwen2.5-Math-7B-Instruct
+        layer_range: [0, 28]
+merge_method: slerp
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
 parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
 dtype: bfloat16
+tokenizer_source: Qwen/Qwen2.5-Coder-7B-Instruct

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tokenizer_config.json CHANGED Viewed

@@ -199,7 +199,7 @@
   "clean_up_tokenization_spaces": false,
   "eos_token": "<|im_end|>",
   "errors": "replace",
-  "model_max_length": 131072,
   "pad_token": "<|endoftext|>",
   "split_special_tokens": false,
   "tokenizer_class": "Qwen2Tokenizer",

   "clean_up_tokenization_spaces": false,
   "eos_token": "<|im_end|>",
   "errors": "replace",
+  "model_max_length": 32768,
   "pad_token": "<|endoftext|>",
   "split_special_tokens": false,
   "tokenizer_class": "Qwen2Tokenizer",