Instructions to use iterateai/Interplay-AppCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use iterateai/Interplay-AppCoder with Transformers:

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

pipe = pipeline("text-generation", model="iterateai/Interplay-AppCoder")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("iterateai/Interplay-AppCoder")
model = AutoModelForCausalLM.from_pretrained("iterateai/Interplay-AppCoder")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use iterateai/Interplay-AppCoder with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/iterateai/Interplay-AppCoder

SGLang

How to use iterateai/Interplay-AppCoder 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 "iterateai/Interplay-AppCoder" \
    --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": "iterateai/Interplay-AppCoder",
		"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 "iterateai/Interplay-AppCoder" \
        --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": "iterateai/Interplay-AppCoder",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use iterateai/Interplay-AppCoder with Docker Model Runner:
```
docker model run hf.co/iterateai/Interplay-AppCoder
```

iterateai commited on Oct 31, 2023

Commit

777ea3f

1 Parent(s): ca9c3c6

Delete config.json

Browse files

Files changed (1) hide show

config.json +0 -39

config.json DELETED Viewed

@@ -1,39 +0,0 @@
-{
-  "_name_or_path": "WizardLM/WizardCoder-15B-V1.0",
-  "activation_function": "gelu",
-  "architectures": [
-    "GPTBigCodeForCausalLM"
-  ],
-  "attention_softmax_in_fp32": true,
-  "attn_pdrop": 0.1,
-  "bos_token_id": 0,
-  "embd_pdrop": 0.1,
-  "eos_token_id": 0,
-  "inference_runner": 0,
-  "initializer_range": 0.02,
-  "layer_norm_epsilon": 1e-05,
-  "max_batch_size": null,
-  "max_sequence_length": null,
-  "model_type": "gpt_bigcode",
-  "multi_query": true,
-  "n_embd": 6144,
-  "n_head": 48,
-  "n_inner": 24576,
-  "n_layer": 40,
-  "n_positions": 8192,
-  "pad_key_length": true,
-  "pre_allocate_kv_cache": false,
-  "resid_pdrop": 0.1,
-  "scale_attention_softmax_in_fp32": true,
-  "scale_attn_weights": true,
-  "summary_activation": null,
-  "summary_first_dropout": 0.1,
-  "summary_proj_to_labels": true,
-  "summary_type": "cls_index",
-  "summary_use_proj": true,
-  "torch_dtype": "bfloat16",
-  "transformers_version": "4.34.1",
-  "use_cache": true,
-  "validate_runner_input": true,
-  "vocab_size": 49153
-}