Text Generation
Transformers
Safetensors
English
glm4_moe_lite
code
agent
agentic
highperformance
Mixture of Experts
mixtureofexperts
glm4.7
fast
reasoning
conversational
Instructions to use aaravriyer193/chimpgpt-coder-elite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aaravriyer193/chimpgpt-coder-elite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aaravriyer193/chimpgpt-coder-elite") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("aaravriyer193/chimpgpt-coder-elite") model = AutoModelForCausalLM.from_pretrained("aaravriyer193/chimpgpt-coder-elite", 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]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use aaravriyer193/chimpgpt-coder-elite with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aaravriyer193/chimpgpt-coder-elite" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aaravriyer193/chimpgpt-coder-elite", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/aaravriyer193/chimpgpt-coder-elite
- SGLang
How to use aaravriyer193/chimpgpt-coder-elite 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 "aaravriyer193/chimpgpt-coder-elite" \ --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": "aaravriyer193/chimpgpt-coder-elite", "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 "aaravriyer193/chimpgpt-coder-elite" \ --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": "aaravriyer193/chimpgpt-coder-elite", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use aaravriyer193/chimpgpt-coder-elite with Docker Model Runner:
docker model run hf.co/aaravriyer193/chimpgpt-coder-elite
Update README.md
Browse files
README.md
CHANGED
|
@@ -36,12 +36,6 @@ base_model:
|
|
| 36 |
=============================================================================
|
| 37 |
````
|
| 38 |
|
| 39 |
-
\<div align="center"\>
|
| 40 |
-
|
| 41 |
-
*Provide concise, bug-free, and high-performance code.*
|
| 42 |
-
|
| 43 |
-
\</div\>
|
| 44 |
-
|
| 45 |
-----
|
| 46 |
|
| 47 |
## 🦍 Overview
|
|
|
|
| 36 |
=============================================================================
|
| 37 |
````
|
| 38 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 39 |
-----
|
| 40 |
|
| 41 |
## 🦍 Overview
|