Text Generation
Safetensors
English
talkie
gptq
4-bit precision
quantized
instruction-tuned
vintage-language-model
chat
custom_code
Instructions to use dtestnyrr/talkie-1930-13b-it-gptq-int4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps Settings
- vLLM
How to use dtestnyrr/talkie-1930-13b-it-gptq-int4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dtestnyrr/talkie-1930-13b-it-gptq-int4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dtestnyrr/talkie-1930-13b-it-gptq-int4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dtestnyrr/talkie-1930-13b-it-gptq-int4
- SGLang
How to use dtestnyrr/talkie-1930-13b-it-gptq-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 "dtestnyrr/talkie-1930-13b-it-gptq-int4" \ --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": "dtestnyrr/talkie-1930-13b-it-gptq-int4", "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 "dtestnyrr/talkie-1930-13b-it-gptq-int4" \ --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": "dtestnyrr/talkie-1930-13b-it-gptq-int4", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dtestnyrr/talkie-1930-13b-it-gptq-int4 with Docker Model Runner:
docker model run hf.co/dtestnyrr/talkie-1930-13b-it-gptq-int4
File size: 948 Bytes
79636b3 | 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 | from transformers import PretrainedConfig
class TalkieConfig(PretrainedConfig):
model_type = "talkie"
def __init__(
self,
vocab_size: int = 65536,
hidden_size: int = 5120,
num_hidden_layers: int = 40,
num_attention_heads: int = 40,
head_dim: int = 128,
intermediate_size: int = 13696,
max_position_embeddings: int = 2048,
rope_theta: float = 1_000_000.0,
tie_word_embeddings: bool = False,
**kwargs,
):
self.vocab_size = vocab_size
self.hidden_size = hidden_size
self.num_hidden_layers = num_hidden_layers
self.num_attention_heads = num_attention_heads
self.head_dim = head_dim
self.intermediate_size = intermediate_size
self.max_position_embeddings = max_position_embeddings
self.rope_theta = rope_theta
super().__init__(tie_word_embeddings=tie_word_embeddings, **kwargs)
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