Text Generation
Transformers
PyTorch
English
chat
cogvlm2
conversational
custom_code
4-bit precision
bitsandbytes
Instructions to use zai-org/cogvlm2-llama3-chat-19B-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/cogvlm2-llama3-chat-19B-int4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="zai-org/cogvlm2-llama3-chat-19B-int4", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("zai-org/cogvlm2-llama3-chat-19B-int4", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use zai-org/cogvlm2-llama3-chat-19B-int4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "zai-org/cogvlm2-llama3-chat-19B-int4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "zai-org/cogvlm2-llama3-chat-19B-int4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/zai-org/cogvlm2-llama3-chat-19B-int4
- SGLang
How to use zai-org/cogvlm2-llama3-chat-19B-int4 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 "zai-org/cogvlm2-llama3-chat-19B-int4" \ --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": "zai-org/cogvlm2-llama3-chat-19B-int4", "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 "zai-org/cogvlm2-llama3-chat-19B-int4" \ --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": "zai-org/cogvlm2-llama3-chat-19B-int4", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use zai-org/cogvlm2-llama3-chat-19B-int4 with Docker Model Runner:
docker model run hf.co/zai-org/cogvlm2-llama3-chat-19B-int4
File size: 1,604 Bytes
119df23 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 | {
"_name_or_path": "/share/official_pretrains/hf_home/cogvlm2-series/cogvlm2-llama3-chat-19B",
"architectures": [
"CogVLMForCausalLM"
],
"auto_map": {
"AutoConfig": "configuration_cogvlm.CogVLMConfig",
"AutoModelForCausalLM": "modeling_cogvlm.CogVLMForCausalLM"
},
"bos_token_id": 128000,
"eos_token_id": [
128001,
128009
],
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 14336,
"max_position_embeddings": 8192,
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_multi_query_heads": 8,
"pad_token_id": 128002,
"quantization_config": {
"_load_in_4bit": true,
"_load_in_8bit": false,
"bnb_4bit_compute_dtype": "float32",
"bnb_4bit_quant_storage": "uint8",
"bnb_4bit_quant_type": "fp4",
"bnb_4bit_use_double_quant": false,
"llm_int8_enable_fp32_cpu_offload": false,
"llm_int8_has_fp16_weight": false,
"llm_int8_skip_modules": null,
"llm_int8_threshold": 6.0,
"load_in_4bit": true,
"load_in_8bit": false,
"quant_method": "bitsandbytes"
},
"rms_norm_eps": 1e-05,
"template_version": "chat",
"tie_word_embeddings": false,
"torch_dtype": "float16",
"transformers_version": "4.42.0.dev0",
"use_cache": true,
"vision_config": {
"dropout_prob": 0.0,
"hidden_act": "gelu",
"hidden_size": 1792,
"image_size": 1344,
"in_channels": 3,
"intermediate_size": 15360,
"layer_norm_eps": 1e-06,
"num_heads": 16,
"num_hidden_layers": 63,
"num_positions": 9217,
"patch_size": 14
},
"vocab_size": 128256
}
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