Instructions to use denizzhansahin/deneme_spor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use denizzhansahin/deneme_spor with Transformers:

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

pipe = pipeline("text-generation", model="denizzhansahin/deneme_spor")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("denizzhansahin/deneme_spor")
model = AutoModelForCausalLM.from_pretrained("denizzhansahin/deneme_spor", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use denizzhansahin/deneme_spor with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/denizzhansahin/deneme_spor

SGLang

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

Docker Model Runner
How to use denizzhansahin/deneme_spor with Docker Model Runner:
```
docker model run hf.co/denizzhansahin/deneme_spor
```

denizzhansahin commited on Apr 11, 2024

Commit

31bb7d4

verified ·

1 Parent(s): e0243ed

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README.md +200 -198
config.json +38 -0
generation_config.json +6 -0
tf_model.h5 +3 -0

README.md CHANGED Viewed

@@ -1,201 +1,203 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-- **Developed by:** [More Information Needed]
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-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
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-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-#### Preprocessing [optional]
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-#### Training Hyperparameters
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-#### Speeds, Sizes, Times [optional]
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
-### Testing Data, Factors & Metrics
-#### Testing Data
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-#### Factors
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-### Results
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-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
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-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-- **Hardware Type:** [More Information Needed]
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 ---
+license: mit
+base_model: gpt2
+tags:
+- generated_from_keras_callback
+model-index:
+- name: deneme_spor
+  results: []
 ---
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+# deneme_spor
+This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Train Loss: 4.9093
+- Validation Loss: 5.9538
+- Epoch: 149
+## Model description
+More information needed
+## Intended uses & limitations
+More information needed
+## Training and evaluation data
+More information needed
+## Training procedure
+### Training hyperparameters
+The following hyperparameters were used during training:
+- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': -963, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
+- training_precision: float32
+### Training results
+| Train Loss | Validation Loss | Epoch |
+|:----------:|:---------------:|:-----:|
+| 9.1978     | 8.9070          | 0     |
+| 8.7400     | 8.5517          | 1     |
+| 8.4947     | 8.3909          | 2     |
+| 8.3502     | 8.2608          | 3     |
+| 8.2126     | 8.1241          | 4     |
+| 8.0688     | 7.9827          | 5     |
+| 7.9232     | 7.8449          | 6     |
+| 7.7844     | 7.7107          | 7     |
+| 7.6446     | 7.5719          | 8     |
+| 7.4919     | 7.4263          | 9     |
+| 7.3429     | 7.2975          | 10    |
+| 7.2042     | 7.1774          | 11    |
+| 7.0643     | 7.0685          | 12    |
+| 6.9229     | 6.9668          | 13    |
+| 6.7836     | 6.8770          | 14    |
+| 6.6425     | 6.7752          | 15    |
+| 6.4982     | 6.6895          | 16    |
+| 6.3539     | 6.5963          | 17    |
+| 6.2035     | 6.5170          | 18    |
+| 6.0612     | 6.4285          | 19    |
+| 5.9164     | 6.3429          | 20    |
+| 5.7708     | 6.2664          | 21    |
+| 5.6249     | 6.1997          | 22    |
+| 5.4822     | 6.1348          | 23    |
+| 5.3368     | 6.0659          | 24    |
+| 5.1959     | 6.0042          | 25    |
+| 5.0527     | 5.9525          | 26    |
+| 4.9070     | 5.9538          | 27    |
+| 4.9062     | 5.9538          | 28    |
+| 4.9095     | 5.9538          | 29    |
+| 4.9056     | 5.9538          | 30    |
+| 4.9111     | 5.9538          | 31    |
+| 4.9080     | 5.9538          | 32    |
+| 4.9072     | 5.9538          | 33    |
+| 4.9063     | 5.9538          | 34    |
+| 4.9086     | 5.9538          | 35    |
+| 4.9081     | 5.9538          | 36    |
+| 4.9115     | 5.9538          | 37    |
+| 4.9052     | 5.9538          | 38    |
+| 4.9073     | 5.9538          | 39    |
+| 4.9064     | 5.9538          | 40    |
+| 4.9096     | 5.9538          | 41    |
+| 4.9093     | 5.9538          | 42    |
+| 4.9077     | 5.9538          | 43    |
+| 4.9078     | 5.9538          | 44    |
+| 4.9073     | 5.9538          | 45    |
+| 4.9076     | 5.9538          | 46    |
+| 4.9096     | 5.9538          | 47    |
+| 4.9093     | 5.9538          | 48    |
+| 4.9093     | 5.9538          | 49    |
+| 4.9082     | 5.9538          | 50    |
+| 4.9106     | 5.9538          | 51    |
+| 4.9076     | 5.9538          | 52    |
+| 4.9079     | 5.9538          | 53    |
+| 4.9093     | 5.9538          | 54    |
+| 4.9096     | 5.9538          | 55    |
+| 4.9063     | 5.9538          | 56    |
+| 4.9071     | 5.9538          | 57    |
+| 4.9122     | 5.9538          | 58    |
+| 4.9108     | 5.9538          | 59    |
+| 4.9072     | 5.9538          | 60    |
+| 4.9073     | 5.9538          | 61    |
+| 4.9085     | 5.9538          | 62    |
+| 4.9080     | 5.9538          | 63    |
+| 4.9092     | 5.9538          | 64    |
+| 4.9077     | 5.9538          | 65    |
+| 4.9087     | 5.9538          | 66    |
+| 4.9073     | 5.9538          | 67    |
+| 4.9078     | 5.9538          | 68    |
+| 4.9102     | 5.9538          | 69    |
+| 4.9095     | 5.9538          | 70    |
+| 4.9099     | 5.9538          | 71    |
+| 4.9081     | 5.9538          | 72    |
+| 4.9089     | 5.9538          | 73    |
+| 4.9068     | 5.9538          | 74    |
+| 4.9091     | 5.9538          | 75    |
+| 4.9078     | 5.9538          | 76    |
+| 4.9083     | 5.9538          | 77    |
+| 4.9067     | 5.9538          | 78    |
+| 4.9077     | 5.9538          | 79    |
+| 4.9111     | 5.9538          | 80    |
+| 4.9088     | 5.9538          | 81    |
+| 4.9085     | 5.9538          | 82    |
+| 4.9093     | 5.9538          | 83    |
+| 4.9086     | 5.9538          | 84    |
+| 4.9088     | 5.9538          | 85    |
+| 4.9057     | 5.9538          | 86    |
+| 4.9104     | 5.9538          | 87    |
+| 4.9081     | 5.9538          | 88    |
+| 4.9070     | 5.9538          | 89    |
+| 4.9076     | 5.9538          | 90    |
+| 4.9078     | 5.9538          | 91    |
+| 4.9097     | 5.9538          | 92    |
+| 4.9082     | 5.9538          | 93    |
+| 4.9061     | 5.9538          | 94    |
+| 4.9111     | 5.9538          | 95    |
+| 4.9067     | 5.9538          | 96    |
+| 4.9070     | 5.9538          | 97    |
+| 4.9089     | 5.9538          | 98    |
+| 4.9051     | 5.9538          | 99    |
+| 4.9072     | 5.9538          | 100   |
+| 4.9110     | 5.9538          | 101   |
+| 4.9094     | 5.9538          | 102   |
+| 4.9089     | 5.9538          | 103   |
+| 4.9072     | 5.9538          | 104   |
+| 4.9072     | 5.9538          | 105   |
+| 4.9055     | 5.9538          | 106   |
+| 4.9079     | 5.9538          | 107   |
+| 4.9075     | 5.9538          | 108   |
+| 4.9100     | 5.9538          | 109   |
+| 4.9106     | 5.9538          | 110   |
+| 4.9081     | 5.9538          | 111   |
+| 4.9094     | 5.9538          | 112   |
+| 4.9108     | 5.9538          | 113   |
+| 4.9082     | 5.9538          | 114   |
+| 4.9089     | 5.9538          | 115   |
+| 4.9099     | 5.9538          | 116   |
+| 4.9063     | 5.9538          | 117   |
+| 4.9094     | 5.9538          | 118   |
+| 4.9059     | 5.9538          | 119   |
+| 4.9096     | 5.9538          | 120   |
+| 4.9065     | 5.9538          | 121   |
+| 4.9092     | 5.9538          | 122   |
+| 4.9092     | 5.9538          | 123   |
+| 4.9107     | 5.9538          | 124   |
+| 4.9061     | 5.9538          | 125   |
+| 4.9117     | 5.9538          | 126   |
+| 4.9087     | 5.9538          | 127   |
+| 4.9062     | 5.9538          | 128   |
+| 4.9105     | 5.9538          | 129   |
+| 4.9093     | 5.9538          | 130   |
+| 4.9078     | 5.9538          | 131   |
+| 4.9067     | 5.9538          | 132   |
+| 4.9104     | 5.9538          | 133   |
+| 4.9065     | 5.9538          | 134   |
+| 4.9077     | 5.9538          | 135   |
+| 4.9101     | 5.9538          | 136   |
+| 4.9063     | 5.9538          | 137   |
+| 4.9091     | 5.9538          | 138   |
+| 4.9100     | 5.9538          | 139   |
+| 4.9101     | 5.9538          | 140   |
+| 4.9057     | 5.9538          | 141   |
+| 4.9080     | 5.9538          | 142   |
+| 4.9076     | 5.9538          | 143   |
+| 4.9085     | 5.9538          | 144   |
+| 4.9071     | 5.9538          | 145   |
+| 4.9107     | 5.9538          | 146   |
+| 4.9102     | 5.9538          | 147   |
+| 4.9071     | 5.9538          | 148   |
+| 4.9093     | 5.9538          | 149   |
+### Framework versions
+- Transformers 4.38.2
+- TensorFlow 2.15.0
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json ADDED Viewed

	@@ -0,0 +1,38 @@

+{
+  "_name_or_path": "gpt2",
+  "activation_function": "gelu_new",
+  "architectures": [
+    "GPT2LMHeadModel"
+  ],
+  "attn_pdrop": 0.1,
+  "bos_token_id": 0,
+  "embd_pdrop": 0.1,
+  "eos_token_id": 0,
+  "initializer_range": 0.02,
+  "layer_norm_epsilon": 1e-05,
+  "model_type": "gpt2",
+  "n_ctx": 100,
+  "n_embd": 768,
+  "n_head": 12,
+  "n_inner": null,
+  "n_layer": 12,
+  "n_positions": 1024,
+  "reorder_and_upcast_attn": false,
+  "resid_pdrop": 0.1,
+  "scale_attn_by_inverse_layer_idx": false,
+  "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,
+  "task_specific_params": {
+    "text-generation": {
+      "do_sample": true,
+      "max_length": 50
+    }
+  },
+  "transformers_version": "4.38.2",
+  "use_cache": true,
+  "vocab_size": 10000
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,6 @@

+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "transformers_version": "4.38.2"
+}

tf_model.h5 ADDED Viewed

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

+version https://git-lfs.github.com/spec/v1
+oid sha256:fadd30c2da3c482f42c85731921c2484079f2e0cf618dbe9a7a28770fc3ab88a
+size 374265936