Instructions to use temporary0-0name/run_opt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use temporary0-0name/run_opt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="temporary0-0name/run_opt")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("temporary0-0name/run_opt") model = AutoModelForCausalLM.from_pretrained("temporary0-0name/run_opt") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use temporary0-0name/run_opt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "temporary0-0name/run_opt" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "temporary0-0name/run_opt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/temporary0-0name/run_opt
- SGLang
How to use temporary0-0name/run_opt 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 "temporary0-0name/run_opt" \ --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": "temporary0-0name/run_opt", "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 "temporary0-0name/run_opt" \ --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": "temporary0-0name/run_opt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use temporary0-0name/run_opt with Docker Model Runner:
docker model run hf.co/temporary0-0name/run_opt
Commit ·
e65daa3
1
Parent(s): efdc87d
End of training
Browse files
README.md
CHANGED
|
@@ -1,6 +1,6 @@
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
-
base_model:
|
| 4 |
tags:
|
| 5 |
- generated_from_trainer
|
| 6 |
datasets:
|
|
@@ -15,9 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 15 |
|
| 16 |
# run_opt
|
| 17 |
|
| 18 |
-
This model is a fine-tuned version of [
|
| 19 |
-
It achieves the following results on the evaluation set:
|
| 20 |
-
- Loss: 0.0107
|
| 21 |
|
| 22 |
## Model description
|
| 23 |
|
|
@@ -45,35 +43,18 @@ The following hyperparameters were used during training:
|
|
| 45 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 46 |
- lr_scheduler_type: cosine
|
| 47 |
- lr_scheduler_warmup_steps: 100
|
| 48 |
-
- num_epochs:
|
| 49 |
|
| 50 |
### Training results
|
| 51 |
|
| 52 |
| Training Loss | Epoch | Step | Validation Loss |
|
| 53 |
|:-------------:|:-----:|:----:|:---------------:|
|
| 54 |
-
|
|
| 55 |
-
| 4.839 | 1.1 | 200 | 2.0385 |
|
| 56 |
-
| 0.9137 | 1.65 | 300 | 0.3108 |
|
| 57 |
-
| 0.171 | 2.2 | 400 | 0.0877 |
|
| 58 |
-
| 0.0542 | 2.75 | 500 | 0.0396 |
|
| 59 |
-
| 0.025 | 3.29 | 600 | 0.0242 |
|
| 60 |
-
| 0.0148 | 3.84 | 700 | 0.0180 |
|
| 61 |
-
| 0.0098 | 4.39 | 800 | 0.0148 |
|
| 62 |
-
| 0.0077 | 4.94 | 900 | 0.0130 |
|
| 63 |
-
| 0.006 | 5.49 | 1000 | 0.0121 |
|
| 64 |
-
| 0.0053 | 6.04 | 1100 | 0.0115 |
|
| 65 |
-
| 0.0045 | 6.59 | 1200 | 0.0112 |
|
| 66 |
-
| 0.0042 | 7.14 | 1300 | 0.0110 |
|
| 67 |
-
| 0.0039 | 7.69 | 1400 | 0.0109 |
|
| 68 |
-
| 0.0038 | 8.24 | 1500 | 0.0108 |
|
| 69 |
-
| 0.0037 | 8.79 | 1600 | 0.0107 |
|
| 70 |
-
| 0.0037 | 9.33 | 1700 | 0.0107 |
|
| 71 |
-
| 0.0036 | 9.88 | 1800 | 0.0107 |
|
| 72 |
|
| 73 |
|
| 74 |
### Framework versions
|
| 75 |
|
| 76 |
-
- Transformers 4.
|
| 77 |
-
- Pytorch
|
| 78 |
-
- Datasets 2.
|
| 79 |
-
- Tokenizers 0.
|
|
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
+
base_model: temporary0-0name/run_opt
|
| 4 |
tags:
|
| 5 |
- generated_from_trainer
|
| 6 |
datasets:
|
|
|
|
| 15 |
|
| 16 |
# run_opt
|
| 17 |
|
| 18 |
+
This model is a fine-tuned version of [temporary0-0name/run_opt](https://huggingface.co/temporary0-0name/run_opt) on the wikitext dataset.
|
|
|
|
|
|
|
| 19 |
|
| 20 |
## Model description
|
| 21 |
|
|
|
|
| 43 |
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 44 |
- lr_scheduler_type: cosine
|
| 45 |
- lr_scheduler_warmup_steps: 100
|
| 46 |
+
- num_epochs: 1
|
| 47 |
|
| 48 |
### Training results
|
| 49 |
|
| 50 |
| Training Loss | Epoch | Step | Validation Loss |
|
| 51 |
|:-------------:|:-----:|:----:|:---------------:|
|
| 52 |
+
| No log | 1.0 | 1 | 10.6189 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 53 |
|
| 54 |
|
| 55 |
### Framework versions
|
| 56 |
|
| 57 |
+
- Transformers 4.35.2
|
| 58 |
+
- Pytorch 2.1.0+cu118
|
| 59 |
+
- Datasets 2.15.0
|
| 60 |
+
- Tokenizers 0.15.0
|
generation_config.json
CHANGED
|
@@ -1,5 +1,5 @@
|
|
| 1 |
{
|
| 2 |
"_from_model_config": true,
|
| 3 |
"pad_token_id": 0,
|
| 4 |
-
"transformers_version": "4.
|
| 5 |
}
|
|
|
|
| 1 |
{
|
| 2 |
"_from_model_config": true,
|
| 3 |
"pad_token_id": 0,
|
| 4 |
+
"transformers_version": "4.35.2"
|
| 5 |
}
|
runs/Nov17_08-54-58_96834e41e131/events.out.tfevents.1700211302.96834e41e131.2204.6
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d65965fdda6a92ab227043c41474dfd25b512246335660b6a5060e15479b3d28
|
| 3 |
+
size 4829
|