Instructions to use CodeGPTPlus/deepseek-coder-1.3b-typescript with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CodeGPTPlus/deepseek-coder-1.3b-typescript with Transformers:

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

pipe = pipeline("text-generation", model="CodeGPTPlus/deepseek-coder-1.3b-typescript")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("CodeGPTPlus/deepseek-coder-1.3b-typescript")
model = AutoModelForCausalLM.from_pretrained("CodeGPTPlus/deepseek-coder-1.3b-typescript")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use CodeGPTPlus/deepseek-coder-1.3b-typescript with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CodeGPTPlus/deepseek-coder-1.3b-typescript"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "CodeGPTPlus/deepseek-coder-1.3b-typescript",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/CodeGPTPlus/deepseek-coder-1.3b-typescript

SGLang

How to use CodeGPTPlus/deepseek-coder-1.3b-typescript 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 "CodeGPTPlus/deepseek-coder-1.3b-typescript" \
    --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": "CodeGPTPlus/deepseek-coder-1.3b-typescript",
		"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 "CodeGPTPlus/deepseek-coder-1.3b-typescript" \
        --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": "CodeGPTPlus/deepseek-coder-1.3b-typescript",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use CodeGPTPlus/deepseek-coder-1.3b-typescript with Docker Model Runner:
```
docker model run hf.co/CodeGPTPlus/deepseek-coder-1.3b-typescript
```

Vokturz commited on Jan 15, 2024

Commit

d7444f2

verified ·

1 Parent(s): f347ebf

End of training

Browse files

Files changed (2) hide show

README.md +30 -1
pytorch_model.bin +3 -0

README.md CHANGED Viewed

@@ -2,6 +2,7 @@
 license: other
 base_model: deepseek-ai/deepseek-coder-1.3b-base
 tags:
 - generated_from_trainer
 model-index:
 - name: deepseek_coder_1.3b_typescript
@@ -105,7 +106,9 @@ special_tokens:
 # deepseek_coder_1.3b_typescript
-This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on an unknown dataset.
 ## Model description
@@ -135,6 +138,32 @@ The following hyperparameters were used during training:
 - lr_scheduler_warmup_steps: 261
 - num_epochs: 1
 ### Framework versions
 - Transformers 4.37.0.dev0

 license: other
 base_model: deepseek-ai/deepseek-coder-1.3b-base
 tags:
+- axolotl
 - generated_from_trainer
 model-index:
 - name: deepseek_coder_1.3b_typescript
 # deepseek_coder_1.3b_typescript
+This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7681
 ## Model description
 - lr_scheduler_warmup_steps: 261
 - num_epochs: 1
+### Training results
+| Training Loss | Epoch | Step  | Validation Loss |
+|:-------------:|:-----:|:-----:|:---------------:|
+| 1.0745        | 0.0   | 1     | 0.8681          |
+| 1.2267        | 0.05  | 1308  | 0.8130          |
+| 1.1594        | 0.1   | 2616  | 0.8018          |
+| 0.7674        | 0.15  | 3924  | 0.7942          |
+| 0.6443        | 0.2   | 5232  | 0.7889          |
+| 0.9155        | 0.25  | 6540  | 0.7847          |
+| 0.7501        | 0.3   | 7848  | 0.7819          |
+| 0.8835        | 0.35  | 9156  | 0.7792          |
+| 0.7261        | 0.4   | 10464 | 0.7769          |
+| 0.9746        | 0.45  | 11772 | 0.7748          |
+| 0.6884        | 0.5   | 13080 | 0.7734          |
+| 0.6104        | 0.55  | 14388 | 0.7722          |
+| 0.8876        | 0.6   | 15696 | 0.7710          |
+| 0.9567        | 0.65  | 17004 | 0.7703          |
+| 0.6915        | 0.7   | 18312 | 0.7696          |
+| 0.8874        | 0.75  | 19620 | 0.7691          |
+| 0.6124        | 0.8   | 20928 | 0.7686          |
+| 0.8147        | 0.85  | 22236 | 0.7684          |
+| 0.8021        | 0.9   | 23544 | 0.7683          |
+| 0.8665        | 0.95  | 24852 | 0.7681          |
 ### Framework versions
 - Transformers 4.37.0.dev0

pytorch_model.bin ADDED Viewed

	@@ -0,0 +1,3 @@

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